title

CS50 2021 in HDR - Lecture 3 - Algorithms

description

This is CS50, Harvard University's Introduction to the intellectual enterprises of computer science and the art of programming. Enroll for free at https://cs50.edx.org/. Slides, source code, and more at https://cs50.harvard.edu/x. Playlist at https://www.youtube.com/playlist?list=PLhQjrBD2T383f9scHRNYJkior2VvYjpSL.
TABLE OF CONTENTS
00:00:00 - Introduction
00:01:17 - Algorithms
00:05:34 - Searching
00:08:17 - Big O Notation
00:12:51 - Common Running Times
00:13:18 - Asymptotic Notation
00:16:50 - Searching Lockers
00:20:46 - Linear Search
00:29:45 - Binary Search
00:37:11 - Sorting and Searching vs. Just Searching
00:41:23 - Implementing Linear Search
00:45:34 - String Comparison
00:54:28 - Storing Data in Arrays
00:59:36 - Structs
01:12:26 - Sorting
01:13:39 - Visualizing Sorts
01:26:22 - Selection Sort
01:34:28 - Bubble Sort
01:43:03 - Comparing Sorts
01:45:23 - Recursion
02:00:54 - Merge Sort
02:15:16 - Sort Race
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LICENSE
CC BY-NC-SA 4.0
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License
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David J. Malan
https://cs.harvard.edu/malan
malan@harvard.edu

detail

{'title': 'CS50 2021 in HDR - Lecture 3 - Algorithms', 'heatmap': [{'end': 906.067, 'start': 737.262, 'weight': 0.718}, {'end': 3794.3, 'start': 3620.308, 'weight': 0.829}, {'end': 6834.454, 'start': 6747.906, 'weight': 0.899}, {'end': 8127.803, 'start': 8068.022, 'weight': 1}], 'summary': 'Covers various topics including arrays, algorithms, algorithm efficiency, binary search, sorting techniques, and merge sort algorithm, emphasizing algorithm implementation, correctness, efficiency, big o notation, and recursion, and providing examples and pseudocode.', 'chapters': [{'end': 461.823, 'segs': [{'end': 266.066, 'src': 'embed', 'start': 242.293, 'weight': 1, 'content': [{'end': 250.538, 'text': 'But the catch is, with a computer that has this memory, even though you, the human concorder, see everything at once, a computer cannot.', 'start': 242.293, 'duration': 8.245}, {'end': 257.142, 'text': "It's better to think of your computer's memory, your phone's memory, or, more specifically, an array of memory like this,", 'start': 250.778, 'duration': 6.364}, {'end': 261.124, 'text': 'as really being a set of closed doors, not unlike lockers in a school.', 'start': 257.142, 'duration': 3.982}, {'end': 266.066, 'text': "And only by opening each of those doors can the computer actually see what's in there.", 'start': 261.664, 'duration': 4.402}], 'summary': 'Computer memory functions like a set of closed doors, requiring individual access to view contents.', 'duration': 23.773, 'max_score': 242.293, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8242293.jpg'}, {'end': 319.94, 'src': 'embed', 'start': 295.526, 'weight': 2, 'content': [{'end': 303.212, 'text': "And just remember that the conventions we've had since last week now is that these arrays are 0 indexed, so to speak.", 'start': 295.526, 'duration': 7.686}, {'end': 307.674, 'text': 'To be 0 indexed just means that the data type starts counting from 0.', 'start': 303.312, 'duration': 4.362}, {'end': 311.995, 'text': 'So this is location 0, 1, 2, 3, 4, 5, 6.', 'start': 307.674, 'duration': 4.321}, {'end': 319.94, 'text': "And notice, even though there are seven total doors here, the rightmost one, of course, is called 6, just because we've started counting at 0.", 'start': 311.996, 'duration': 7.944}], 'summary': 'Arrays are 0 indexed, meaning data type starts counting from 0. total doors 7, rightmost door is called 6.', 'duration': 24.414, 'max_score': 295.526, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8295526.jpg'}, {'end': 445.274, 'src': 'embed', 'start': 398.511, 'weight': 0, 'content': [{'end': 406.093, 'text': "let's consider how we might lay the foundation of comparing whether one algorithm is better than another.", 'start': 398.511, 'duration': 7.582}, {'end': 407.373, 'text': 'We talked about correctness.', 'start': 406.213, 'duration': 1.16}, {'end': 412.414, 'text': 'And it sort of goes without saying that any code you write, any algorithm you implement had better be correct.', 'start': 407.413, 'duration': 5.001}, {'end': 416.956, 'text': "Otherwise, what's the point if it doesn't give you the right answers? But we also talked about design.", 'start': 412.454, 'duration': 4.502}, {'end': 423.517, 'text': 'And, in your own words, what do we mean when we say a program is better designed at this stage than another?', 'start': 417.436, 'duration': 6.081}, {'end': 428.139, 'text': 'How do you think about this notion of design now? Yeah,', 'start': 424.358, 'duration': 3.781}, {'end': 432.8, 'text': 'OK, so easier to understand.', 'start': 431.297, 'duration': 1.503}, {'end': 433.421, 'text': 'I like that.', 'start': 432.86, 'duration': 0.561}, {'end': 435.405, 'text': 'Other thoughts? Yeah? Efficiency.', 'start': 433.962, 'duration': 1.443}, {'end': 436.086, 'text': 'DAVID J.', 'start': 435.465, 'duration': 0.621}, {'end': 445.274, 'text': "Efficiency And what do you mean by efficiency, precisely? Nice, it doesn't use up too much memory, and it isn't redundant.", 'start': 436.086, 'duration': 9.188}], 'summary': 'Comparing algorithms for correctness, design, and efficiency in terms of memory usage and redundancy.', 'duration': 46.763, 'max_score': 398.511, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8398511.jpg'}], 'start': 11.303, 'title': 'Arrays, algorithms, and algorithm design', 'summary': 'Includes topics like memory representation, arrays, and search algorithms, as well as the 0-indexed convention. it also emphasizes the importance of algorithm implementation, correctness, and efficient design in program development and performance.', 'chapters': [{'end': 356.758, 'start': 11.303, 'title': 'Cs50 week 3: arrays and algorithms', 'summary': 'Covers the representation of memory, arrays, and the process of inputs becoming outputs, emphasizing the importance of search algorithms in programming, as well as the 0-indexed convention for arrays.', 'duration': 345.455, 'highlights': ['The chapter emphasizes the process of inputs becoming outputs and the importance of search algorithms in programming, which is omnipresent in any device.', 'The representation of memory is explained, with the concept of memory being likened to a set of closed doors that a computer must methodically open to access data.', 'The concept of arrays is explored, with an emphasis on the 0-indexed convention, where the data type starts counting from 0.', 'The chapter explains the concept of arrays as contiguous memory and introduces the idea of using loops and conditions to methodically access array elements for searching.']}, {'end': 461.823, 'start': 356.798, 'title': 'Algorithms and design', 'summary': 'Discusses the implementation of algorithms by tech giants, emphasizing the importance of correctness and efficient design in program development and performance.', 'duration': 105.025, 'highlights': ["Efficiency and correctness are crucial in algorithm implementation, as they determine the quality of the program's performance and output.", 'The chapter emphasizes the significance of efficient design, which encompasses aspects like memory usage and redundancy, in developing sophisticated and longer programs.', 'The discussion also focuses on comparing the quality of algorithms, addressing the importance of understanding and evaluating their design and performance.']}], 'duration': 450.52, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x811303.jpg', 'highlights': ['The chapter emphasizes the importance of search algorithms in programming.', 'The representation of memory is explained, likening it to a set of closed doors that a computer must methodically open to access data.', 'The concept of arrays is explored, emphasizing the 0-indexed convention.', "Efficiency and correctness are crucial in algorithm implementation, determining the program's performance and output.", 'The chapter emphasizes the significance of efficient design, encompassing aspects like memory usage and redundancy.']}, {'end': 1740.822, 'segs': [{'end': 490.3, 'src': 'embed', 'start': 461.823, 'weight': 1, 'content': [{'end': 468.387, 'text': 'getting the design right is just going to make it easier to collaborate and ultimately produce right code with just higher probability.', 'start': 461.823, 'duration': 6.564}, {'end': 474.33, 'text': "So let's consider how we might focus on exactly the second characteristic, the efficiency of an algorithm.", 'start': 468.587, 'duration': 5.743}, {'end': 481.074, 'text': 'And the way we might talk about the efficiency of algorithms, just how fast or how slow they are, is in terms of their running time.', 'start': 474.35, 'duration': 6.724}, {'end': 484.656, 'text': "That is to say, when they're running, how much time do they take?", 'start': 481.454, 'duration': 3.202}, {'end': 490.3, 'text': 'And we might measure this in seconds or milliseconds, or minutes, or just some number of steps in the general case,', 'start': 484.796, 'duration': 5.504}], 'summary': 'Design impacts collaboration and code production. focus on algorithm efficiency by measuring running time.', 'duration': 28.477, 'max_score': 461.823, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8461823.jpg'}, {'end': 526.753, 'src': 'embed', 'start': 499.607, 'weight': 0, 'content': [{'end': 505.334, 'text': 'So computer scientists tend to describe the running time of an algorithm, or a piece of code, for that matter,', 'start': 499.607, 'duration': 5.727}, {'end': 507.636, 'text': "in terms of what's called big O notation.", 'start': 505.334, 'duration': 2.302}, {'end': 510.759, 'text': 'This is literally a capitalized O, a big O.', 'start': 507.916, 'duration': 2.843}, {'end': 516.445, 'text': 'And this generally means that the running time of some algorithm is on the order of such and such.', 'start': 510.759, 'duration': 5.686}, {'end': 520.107, 'text': "where such and such, we'll see, is just going to be a very simple mathematical formula.", 'start': 516.445, 'duration': 3.662}, {'end': 526.753, 'text': "It's kind of a way of waving your hands mathematically to convey the idea of just how fast or how slow some algorithm or code is,", 'start': 520.128, 'duration': 6.625}], 'summary': 'Computer scientists use big o notation to describe algorithm running time.', 'duration': 27.146, 'max_score': 499.607, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8499607.jpg'}, {'end': 639.826, 'src': 'embed', 'start': 607.97, 'weight': 2, 'content': [{'end': 615.132, 'text': 'If we had n pages in that phone book, n just representing a generic number, the first algorithm here we might describe as taking n steps.', 'start': 607.97, 'duration': 7.162}, {'end': 622.775, 'text': 'Second algorithm we might describe as taking n divided by 2 steps, maybe give or take 1 if we have to double back, but generally n divided by 2.', 'start': 615.693, 'duration': 7.082}, {'end': 629.777, 'text': 'And then this thing, if you remember your logarithms, was sort of a fundamentally different formula, log base 2 of n, or just log of n for short.', 'start': 622.775, 'duration': 7.002}, {'end': 632.458, 'text': 'So this is sort of a fundamentally different formula.', 'start': 630.117, 'duration': 2.341}, {'end': 639.826, 'text': "But what's noteworthy is that these first two algorithms even though, yes, the second algorithm was hands down faster,", 'start': 632.958, 'duration': 6.868}], 'summary': 'Comparison of algorithms: first takes n steps, second takes n/2, and log base 2 of n for the third.', 'duration': 31.856, 'max_score': 607.97, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8607970.jpg'}, {'end': 906.067, 'src': 'heatmap', 'start': 737.262, 'weight': 0.718, 'content': [{'end': 746.768, 'text': 'If any of you have implemented a for loop at this point in any of your code and that for loop iterated n times where maybe n was the height of your pyramid,', 'start': 737.262, 'duration': 9.506}, {'end': 756.535, 'text': 'or maybe n was something else that you wanted to do n times you wrote code or you implemented an algorithm that operated in big O of n time,', 'start': 746.768, 'duration': 9.767}, {'end': 756.995, 'text': 'if you will.', 'start': 756.535, 'duration': 0.46}, {'end': 765.341, 'text': "So this is just a way now to retroactively start describing with somewhat mathematical notation what we've been doing in practice for a while now.", 'start': 757.095, 'duration': 8.246}, {'end': 771.385, 'text': 'commonly seen running times in the real world.', 'start': 767.922, 'duration': 3.463}, {'end': 777.648, 'text': 'This is not a thorough list, because you could come up with an infinite number of mathematical formulas, certainly.', 'start': 771.485, 'duration': 6.163}, {'end': 784.172, 'text': "But the common ones we'll discuss and you will see in your own code probably reduce to this list here.", 'start': 777.668, 'duration': 6.504}, {'end': 787.634, 'text': 'And if you were to study more computer science theory, this list would get longer and longer.', 'start': 784.212, 'duration': 3.422}, {'end': 791.297, 'text': "But for now, these are sort of the most familiar ones that we'll soon see.", 'start': 787.674, 'duration': 3.623}, {'end': 795.859, 'text': 'All right, two other pieces of vocabulary, if you will, before we start to use this stuff.', 'start': 791.857, 'duration': 4.002}, {'end': 804.944, 'text': 'So this, a big omega, capital omega symbol, is used now to describe a lower bound on the running time of an algorithm.', 'start': 796.339, 'duration': 8.605}, {'end': 812.128, 'text': 'So to be clear, big O is on the order of, that is, an upper bound on how many steps an algorithm might take.', 'start': 805.064, 'duration': 7.064}, {'end': 814.585, 'text': 'on the order of so many steps.', 'start': 812.924, 'duration': 1.661}, {'end': 819.628, 'text': 'If you want to talk, though, from the other perspective, well, how few steps might my algorithm take??', 'start': 814.705, 'duration': 4.923}, {'end': 821.709, 'text': 'Maybe in the so-called best case?', 'start': 819.668, 'duration': 2.041}, {'end': 829.494, 'text': "it'd be nice if we had a notation to just describe what a lower bound is, because some algorithms might be super fast in these so-called best cases.", 'start': 821.709, 'duration': 7.785}, {'end': 834.417, 'text': 'So the symbology is almost the same, but we replace the big O with a big omega.', 'start': 829.934, 'duration': 4.483}, {'end': 840, 'text': 'So to be clear, big O describes an upper bound, and omega describes a lower bound.', 'start': 834.877, 'duration': 5.123}, {'end': 842.162, 'text': "And we'll see examples of this before long.", 'start': 840.08, 'duration': 2.082}, {'end': 844.544, 'text': 'And then lastly, last one.', 'start': 842.802, 'duration': 1.742}, {'end': 855.753, 'text': "here big theta is used by a computer scientist when you have a case where both the upper bound on an algorithm's running time is the same as the lower bound.", 'start': 844.544, 'duration': 11.209}, {'end': 862.9, 'text': "You can then describe it in one breath as being in theta of such and such instead of saying it's in big O and in omega of something else.", 'start': 855.894, 'duration': 7.006}, {'end': 872.115, 'text': 'All right, so out of context, just seemingly cryptic symbols, but all they refer to is upper bounds, lower bounds or, when they happen to be,', 'start': 863.669, 'duration': 8.446}, {'end': 872.696, 'text': 'one and the same.', 'start': 872.115, 'duration': 0.581}, {'end': 878.841, 'text': "And we'll now introduce over time examples of how we might actually apply these to concrete problems.", 'start': 872.736, 'duration': 6.105}, {'end': 881.943, 'text': "But first, let me pause to see if there's any questions.", 'start': 878.981, 'duration': 2.962}, {'end': 890.049, 'text': 'Any questions here? Any questions? I see pointing somewhere.', 'start': 883.284, 'duration': 6.765}, {'end': 894.023, 'text': 'Where are you pointing to? Over here.', 'start': 890.99, 'duration': 3.033}, {'end': 894.443, 'text': 'There we go.', 'start': 894.063, 'duration': 0.38}, {'end': 894.763, 'text': 'OK, sorry.', 'start': 894.543, 'duration': 0.22}, {'end': 895.064, 'text': 'Very bright.', 'start': 894.803, 'duration': 0.261}, {'end': 901.325, 'text': 'So smaller? DAVID MALANI- Smaller n functions move faster.', 'start': 895.084, 'duration': 6.241}, {'end': 906.067, 'text': 'So yes, if you have something like n, that takes only n steps.', 'start': 901.425, 'duration': 4.642}], 'summary': 'The transcript discusses the implementation of for loops and the use of big o, big omega, and big theta symbols to describe the running time of algorithms in computer science.', 'duration': 168.805, 'max_score': 737.262, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8737262.jpg'}, {'end': 956.526, 'src': 'embed', 'start': 931.806, 'weight': 4, 'content': [{'end': 939.912, 'text': 'When an algorithm is on the order of a single step, that means it literally takes constant time one step or maybe 10 steps, 100 steps,', 'start': 931.806, 'duration': 8.106}, {'end': 942.254, 'text': 'but a fixed constant number of steps.', 'start': 939.912, 'duration': 2.342}, {'end': 950.34, 'text': "That's the best, because even as the phone book gets bigger, even as the data set you're searching gets larger and larger.", 'start': 942.594, 'duration': 7.746}, {'end': 956.526, 'text': "if something only takes a finite number of steps constantly, then it doesn't matter how big the data set actually gets.", 'start': 950.34, 'duration': 6.186}], 'summary': "An algorithm that takes a fixed constant number of steps is the best, as it doesn't matter how big the data set gets.", 'duration': 24.72, 'max_score': 931.806, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8931806.jpg'}, {'end': 1170.473, 'src': 'embed', 'start': 1141.588, 'weight': 7, 'content': [{'end': 1142.889, 'text': 'I mean, I do think it was correct.', 'start': 1141.588, 'duration': 1.301}, {'end': 1145.571, 'text': 'Because even though it was slow, you eventually found zero.', 'start': 1142.909, 'duration': 2.662}, {'end': 1148.033, 'text': 'But it took some number of steps.', 'start': 1146.151, 'duration': 1.882}, {'end': 1150.235, 'text': 'So in fact, this would be an algorithm.', 'start': 1148.593, 'duration': 1.642}, {'end': 1152.257, 'text': 'It has a name called linear search.', 'start': 1150.275, 'duration': 1.982}, {'end': 1156.422, 'text': 'And Damir, as you did, you kind of walked along a line going from left to right.', 'start': 1152.317, 'duration': 4.105}, {'end': 1163.31, 'text': 'Now let me ask, if you had gone from right to left, would the algorithm have been fundamentally better? Yes.', 'start': 1156.743, 'duration': 6.567}, {'end': 1163.89, 'text': 'DAVID J.', 'start': 1163.33, 'duration': 0.56}, {'end': 1167.211, 'text': 'OK And why? Because the 0 is here in the first scenario.', 'start': 1163.89, 'duration': 3.321}, {'end': 1170.473, 'text': "But then if it was like the 0 is in the middle, it wouldn't have been.", 'start': 1167.231, 'duration': 3.242}], 'summary': 'Linear search algorithm finds zero after some steps. direction affects efficiency.', 'duration': 28.885, 'max_score': 1141.588, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x81141588.jpg'}, {'end': 1235.019, 'src': 'embed', 'start': 1207.389, 'weight': 6, 'content': [{'end': 1212.792, 'text': "Linear search is about as good as you can do when you don't know anything a priori about the numbers.", 'start': 1207.389, 'duration': 5.403}, {'end': 1215.753, 'text': 'So I have a little thank you gift here, a little CS50 stress ball.', 'start': 1213.032, 'duration': 2.721}, {'end': 1217.533, 'text': 'A round of applause for our first volunteer.', 'start': 1215.793, 'duration': 1.74}, {'end': 1219.294, 'text': 'Thank you so much.', 'start': 1218.654, 'duration': 0.64}, {'end': 1227.636, 'text': "Let's try to formalize what I just described as linear search.", 'start': 1223.755, 'duration': 3.881}, {'end': 1235.019, 'text': 'Because indeed, no matter which N Namir had started on, I could have kind of changed up the problem to make sure that it appears to be running slow.', 'start': 1227.676, 'duration': 7.343}], 'summary': 'Linear search is a basic method when no prior knowledge is available, demonstrated with a stress ball giveaway and a volunteer.', 'duration': 27.63, 'max_score': 1207.389, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x81207389.jpg'}, {'end': 1705.032, 'src': 'embed', 'start': 1675.166, 'weight': 9, 'content': [{'end': 1676.647, 'text': "But it's a constant number of steps.", 'start': 1675.166, 'duration': 1.481}, {'end': 1681.248, 'text': 'And the way we describe constant number of steps is just with a single number, like 1.', 'start': 1676.687, 'duration': 4.561}, {'end': 1688.431, 'text': 'So the omega notation for linear search might be omega of 1, because in the best case, she might just get the number right from the get-go.', 'start': 1681.248, 'duration': 7.183}, {'end': 1693.453, 'text': 'But in the worst case, we need to talk about the upper bound, which might indeed be big O of n.', 'start': 1688.771, 'duration': 4.682}, {'end': 1701.466, 'text': "So again, there's this way now of talking symbolically about best cases and worst cases or lower bounds and upper bounds.", 'start': 1694.153, 'duration': 7.313}, {'end': 1705.032, 'text': 'Theta notation, just as a little trivia now.', 'start': 1701.486, 'duration': 3.546}], 'summary': 'Linear search has omega of 1 and big o of n in best and worst cases, respectively.', 'duration': 29.866, 'max_score': 1675.166, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x81675166.jpg'}], 'start': 461.823, 'title': 'Algorithm efficiency and phone book algorithms', 'summary': 'Discusses the importance of algorithm efficiency measured using big o notation and compares running times of different phone book algorithms, where the first takes n steps, the second takes n/2 steps, and the third takes log base 2 of n steps. it explains big o notation, big omega, and big theta, and illustrates how algorithm size affects speed and efficiency, with smaller n functions moving faster and constant time being optimal. it also covers the linear search algorithm and its analysis, highlighting trade-offs between correctness and efficiency, and providing upper and lower bounds for running time.', 'chapters': [{'end': 537.281, 'start': 461.823, 'title': 'Algorithm efficiency and big o notation', 'summary': 'Discusses the importance of design in collaboration and code production, focusing on algorithm efficiency measured in terms of running time using big o notation.', 'duration': 75.458, 'highlights': ['The running time of an algorithm is described using big O notation, conveying the idea of how fast or slow the algorithm or code is, without specifying the exact time or number of steps.', 'Efficient design leads to easier collaboration and a higher probability of producing correct code.']}, {'end': 1018.364, 'start': 537.341, 'title': 'Phone book algorithms and running time', 'summary': 'Discusses different phone book algorithms, comparing their running times, where the first algorithm takes n steps, the second takes n divided by 2 steps, and the third takes log base 2 of n steps. it also introduces big o notation to describe the running time of algorithms and explains the concepts of big omega and big theta. finally, it illustrates how the size of an algorithm affects its speed and efficiency, with smaller n functions moving faster and constant time being the optimal scenario.', 'duration': 481.023, 'highlights': ['The third algorithm takes log base 2 of n steps, significantly reducing the problem size with each iteration, taking 500 pages the first time, another 250, another 125, versus just one or two bytes at a time. The third algorithm, using the divide and conquer strategy, reduces the problem size significantly with each iteration, taking 500 pages the first time, another 250, another 125, versus just one or two bytes at a time.', 'The second algorithm takes n divided by 2 steps, making it hands down faster than the first algorithm. The second algorithm is significantly faster than the first one, taking n divided by 2 steps.', 'Big O notation is introduced to describe the running time of algorithms, with the first two algorithms being on the order of n steps and the third algorithm being on the order of log n steps. Big O notation is introduced to describe the running time of algorithms, with the first two algorithms being on the order of n steps and the third algorithm being on the order of log n steps.', 'Constant time, represented by big O notation or even theta, implies that an algorithm takes a fixed number of steps, regardless of the size of the data set, making it the optimal scenario for efficiency. Constant time, represented by big O notation or even theta, implies that an algorithm takes a fixed number of steps, regardless of the size of the data set, making it the optimal scenario for efficiency.', 'The chapter discusses different phone book algorithms, comparing their running times, where the first algorithm takes n steps, the second takes n divided by 2 steps, and the third takes log base 2 of n steps. The chapter discusses different phone book algorithms, comparing their running times, where the first algorithm takes n steps, the second takes n divided by 2 steps, and the third takes log base 2 of n steps.']}, {'end': 1314.751, 'start': 1018.384, 'title': 'Linear search algorithm', 'summary': 'Explains the linear search algorithm, where a volunteer demonstrates the process of finding a specific number in an array of memory, highlighting the trade-offs between correctness and efficiency, and the applicability of linear search when the order of numbers is unknown.', 'duration': 296.367, 'highlights': ['The chapter explains the linear search algorithm, where a volunteer demonstrates the process of finding a specific number in an array of memory. The chapter introduces the concept of linear search through a demonstration with a volunteer, Namira, tasked with finding a specific number in an array of memory.', 'Highlighting the trade-offs between correctness and efficiency in the linear search algorithm. The chapter discusses the trade-offs between correctness and efficiency in the linear search algorithm, highlighting the contrast between a slow but correct algorithm and the need for more efficient solutions.', 'The applicability of linear search when the order of numbers is unknown. The chapter explains the applicability of linear search when the order of numbers is unknown, emphasizing that it is a suitable approach when no information is available about the order of the numbers in the array.']}, {'end': 1740.822, 'start': 1315.112, 'title': 'Linear search algorithm analysis', 'summary': "Discusses the linear search algorithm, analyzing its running time and efficiency in terms of big o notation, omega notation, and theta notation, highlighting the number of steps for each operation and providing an upper and lower bound for the algorithm's running time.", 'duration': 425.71, 'highlights': ['The linear search algorithm operates with an upper bound running time of big O of n, as it essentially performs n steps in the worst case scenario when searching for a number among n elements. In the worst-case scenario, the algorithm performs n steps to search for the number among n elements, resulting in an upper bound running time of big O of n.', 'In the best case scenario, the linear search algorithm operates with a lower bound running time of omega of 1, as it may find the desired number in just one step. In the best-case scenario, the algorithm may find the desired number in just one step, resulting in a lower bound running time of omega of 1.', "The analysis of the algorithm's running time involves considering the number of steps for each operation, with the loop operating n times and the inner steps taking a constant number of steps each. The analysis involves considering the loop operating n times and the inner steps taking a constant number of steps each, which impacts the overall running time of the algorithm."]}], 'duration': 1278.999, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x8461823.jpg', 'highlights': ['Big O notation describes algorithm running time without specifying exact steps.', 'Efficient design leads to easier collaboration and higher probability of correct code.', 'Third algorithm takes log base 2 of n steps, significantly reducing problem size.', 'Second algorithm takes n/2 steps, making it significantly faster than the first.', 'Constant time implies fixed steps, optimal for efficiency.', "Chapter discusses phone book algorithms' running times: n, n/2, log base 2 of n steps.", 'Chapter introduces linear search algorithm through demonstration with volunteer.', 'Trade-offs between correctness and efficiency in linear search algorithm are highlighted.', 'Linear search is applicable when the order of numbers is unknown.', 'Linear search has upper bound running time of big O of n and lower bound running time of omega of 1.', "Algorithm's running time analysis involves considering number of steps for each operation."]}, {'end': 2285.866, 'segs': [{'end': 1956.129, 'src': 'embed', 'start': 1893.968, 'weight': 0, 'content': [{'end': 1899.83, 'text': "then by going to the left half, which we're able to find in just three steps instead of seven,", 'start': 1893.968, 'duration': 5.862}, {'end': 1903.511, 'text': 'the number six in this case that we were actually searching for.', 'start': 1899.83, 'duration': 3.681}, {'end': 1906.993, 'text': 'So you can see that this would seem to be more efficient.', 'start': 1903.632, 'duration': 3.361}, {'end': 1916.379, 'text': "Let's consider for just a moment is it correct? if I had used different numbers but still sorted them from left to right,", 'start': 1907.833, 'duration': 8.546}, {'end': 1919.603, 'text': 'would it still have worked this algorithm??', 'start': 1916.379, 'duration': 3.224}, {'end': 1920.343, 'text': "You're nodding your head.", 'start': 1919.623, 'duration': 0.72}, {'end': 1922.706, 'text': 'Can I call on you? Like, why would it still have worked, do you think??', 'start': 1920.363, 'duration': 2.343}, {'end': 1932.418, 'text': 'Yeah, so, so long as the numbers are always in the same order from left to right, or heck, they could even be in reverse order.', 'start': 1927.096, 'duration': 5.322}, {'end': 1940.622, 'text': "so long as it's consistent, the decisions that Rave was making, if greater than else, if less than, would guide us to the solution, no matter what.", 'start': 1932.418, 'duration': 8.204}, {'end': 1943.243, 'text': 'And it would seem to take fewer steps.', 'start': 1940.742, 'duration': 2.501}, {'end': 1948.365, 'text': "So if we consider now the pseudocode for this algorithm, let's take a look how we might describe binary search.", 'start': 1943.343, 'duration': 5.022}, {'end': 1951.026, 'text': 'So binary search we might describe with something like this.', 'start': 1948.405, 'duration': 2.621}, {'end': 1956.129, 'text': 'If the number is behind the middle door, which is where Rave began, then we can just return true.', 'start': 1951.587, 'duration': 4.542}], 'summary': 'Binary search algorithm finds number in 3 steps, more efficient and consistent in any order.', 'duration': 62.161, 'max_score': 1893.968, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x81893968.jpg'}, {'end': 2185.344, 'src': 'embed', 'start': 2140.546, 'weight': 3, 'content': [{'end': 2150.293, 'text': 'So we might say that, indeed, binary search is in big O of log n, because the door that Rave opened last, this one, happened to be three doors away.', 'start': 2140.546, 'duration': 9.747}, {'end': 2154.396, 'text': 'And actually, if you do the math here, that roughly works out to be exactly that case.', 'start': 2150.333, 'duration': 4.063}, {'end': 2161.641, 'text': "If we add one, it's sort of out of seven doors, or roughly eight, we were able to search it in just three total steps.", 'start': 2154.476, 'duration': 7.165}, {'end': 2167.165, 'text': 'What about omega notation, though? Like, in the best case, Rafe might have gotten lucky.', 'start': 2162.041, 'duration': 5.124}, {'end': 2168.947, 'text': 'She opened the door, and there it is.', 'start': 2167.225, 'duration': 1.722}, {'end': 2176.554, 'text': 'So how might we describe a lower bound on the running time of binary search? Yeah? DAVID J.', 'start': 2169.247, 'duration': 7.307}, {'end': 2179.458, 'text': 'Say again? omega of 1.', 'start': 2176.554, 'duration': 2.904}, {'end': 2185.344, 'text': "So here, too, we see that in some cases, binary search and linear search, eh, they're pretty equivalent.", 'start': 2179.458, 'duration': 5.886}], 'summary': 'Binary search is in big o of log n, with best case scenario of omega of 1.', 'duration': 44.798, 'max_score': 2140.546, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x82140546.jpg'}, {'end': 2222.831, 'src': 'embed', 'start': 2201.338, 'weight': 5, 'content': [{'end': 2210.524, 'text': 'How long am I going to be sitting there watching some spinning hourglass or a beach ball trying to give myself an answer to a pretty big problem?', 'start': 2201.338, 'duration': 9.186}, {'end': 2213.465, 'text': "Well, odds are, you're going to generally care about big O notation.", 'start': 2210.904, 'duration': 2.561}, {'end': 2220.449, 'text': "So indeed, moving forward, we'll generally talk about the running time of algorithms, often in terms of big O, a little less so in terms of omega.", 'start': 2213.505, 'duration': 6.944}, {'end': 2222.831, 'text': 'But understanding the range can be important.', 'start': 2220.87, 'duration': 1.961}], 'summary': 'Understanding big o notation is important for analyzing algorithm running time.', 'duration': 21.493, 'max_score': 2201.338, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x82201338.jpg'}], 'start': 1740.882, 'title': 'Efficiency of binary search algorithm', 'summary': 'Discusses the efficiency of the binary search algorithm, highlighting its ability to find the desired number in fewer steps, demonstrating a consistent decision-making process, and outlining the pseudocode. it also covers worst and best case scenarios, and the significance of big o notation in determining algorithm efficiency.', 'chapters': [{'end': 1975.685, 'start': 1740.882, 'title': 'Efficiency of binary search algorithm', 'summary': 'Discusses the efficiency of the binary search algorithm, highlighting its ability to find the desired number in fewer steps by dividing and conquering based on sorted numbers, demonstrating a consistent decision-making process, and outlining the pseudocode for the algorithm.', 'duration': 234.803, 'highlights': ['The binary search algorithm demonstrated greater efficiency by finding the number in just three steps instead of seven, showcasing the advantage of dividing and conquering based on sorted numbers. Rave was able to find the desired number in just three steps, highlighting the efficiency of the binary search algorithm compared to traditional search methods.', "Consistent decision-making based on the order of numbers, whether in ascending or descending order, ensures the success of the binary search algorithm and reduces the number of steps required to find the desired number. The chapter emphasizes that as long as the order of numbers is consistent, the binary search algorithm's decision-making process remains effective, showcasing its adaptability to different sorted orders and its ability to reduce the number of steps needed for finding the desired number.", "The pseudocode for binary search involves checking if the number is behind the middle door, searching the left or right half based on the comparison with the middle door, and handling scenarios where there are no doors, providing a clear outline of the algorithm's decision-making process. The chapter outlines the pseudocode for the binary search algorithm, providing a clear structure for the decision-making process involved in finding the desired number and demonstrating the algorithm's logic for handling various scenarios during the search."]}, {'end': 2285.866, 'start': 1975.685, 'title': 'Binary search algorithm', 'summary': 'Discusses the efficiency of binary search algorithm, demonstrating its worst and best case scenarios, and the significance of big o notation in determining algorithm efficiency.', 'duration': 310.181, 'highlights': ["Binary search algorithm's worst case time complexity is O(log n) The worst case time complexity of binary search algorithm is O(log n), where the algorithm can divide the problem in half log n times before finding the solution.", "Binary search algorithm's best case time complexity is Ω(1) The best case time complexity of binary search algorithm is Ω(1), where the algorithm might find the solution in constant time, making it very efficient in certain scenarios.", 'Importance of big O notation in analyzing algorithm efficiency The significance of big O notation is highlighted in determining the running time of algorithms, where worst case scenarios are crucial to consider in order to understand how long an algorithm might take to solve a problem.']}], 'duration': 544.984, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x81740882.jpg', 'highlights': ['The binary search algorithm demonstrated greater efficiency by finding the number in just three steps instead of seven, showcasing the advantage of dividing and conquering based on sorted numbers.', 'Consistent decision-making based on the order of numbers ensures the success of the binary search algorithm and reduces the number of steps required to find the desired number.', "The pseudocode for binary search involves checking if the number is behind the middle door, searching the left or right half based on the comparison with the middle door, and handling scenarios where there are no doors, providing a clear outline of the algorithm's decision-making process.", "Binary search algorithm's worst case time complexity is O(log n), where the algorithm can divide the problem in half log n times before finding the solution.", "Binary search algorithm's best case time complexity is Ω(1), where the algorithm might find the solution in constant time, making it very efficient in certain scenarios.", 'The significance of big O notation is highlighted in determining the running time of algorithms, where worst case scenarios are crucial to consider in order to understand how long an algorithm might take to solve a problem.']}, {'end': 3376.879, 'segs': [{'end': 2320.527, 'src': 'embed', 'start': 2285.866, 'weight': 0, 'content': [{'end': 2290.769, 'text': 'and then search? Or should you just dive right in and search it linearly?', 'start': 2285.866, 'duration': 4.903}, {'end': 2297.667, 'text': "Like, how might you think about that? If you are Google, for instance, and you've got millions, billions of web pages,", 'start': 2291.903, 'duration': 5.764}, {'end': 2301.51, 'text': "should they just go with linear search, because it's always going to work, even though it might be slow?", 'start': 2297.667, 'duration': 3.843}, {'end': 2304.693, 'text': 'Or should they invest the time in sorting all of that data?', 'start': 2302.131, 'duration': 2.562}, {'end': 2305.814, 'text': "We'll see how in a bit.", 'start': 2304.773, 'duration': 1.041}, {'end': 2308.436, 'text': 'And then search it more efficiently.', 'start': 2306.694, 'duration': 1.742}, {'end': 2320.527, 'text': "Like, how do you decide between those options? Yeah, if you had to sort the data first, and we don't yet formally know how to do this.", 'start': 2308.956, 'duration': 11.571}], 'summary': 'How should google search: linearly or invest time in sorting data for efficiency?', 'duration': 34.661, 'max_score': 2285.866, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x82285866.jpg'}, {'end': 2505.868, 'src': 'embed', 'start': 2474.106, 'weight': 1, 'content': [{'end': 2475.948, 'text': "And when we come back, we'll write some actual code.", 'start': 2474.106, 'duration': 1.842}, {'end': 2482.554, 'text': "So we've seen a couple searches, linear search and binary search, which, to be fair, we saw back in week 0.", 'start': 2477.21, 'duration': 5.344}, {'end': 2489.878, 'text': "But let's actually translate at least one of those now to some code, using this building block from last week, where we can actually define an array,", 'start': 2482.554, 'duration': 7.324}, {'end': 2492.66, 'text': 'if we want, like an array of integers called numbers.', 'start': 2489.878, 'duration': 2.782}, {'end': 2494.221, 'text': 'So let me switch over to VS Code here.', 'start': 2492.72, 'duration': 1.501}, {'end': 2497.563, 'text': 'Let me go ahead and start a program called numbers.c.', 'start': 2494.601, 'duration': 2.962}, {'end': 2505.868, 'text': "And in numbers.c, let me go ahead here and How about let's include our familiar header file, so cs50.h.", 'start': 2498.124, 'duration': 7.744}], 'summary': 'Transcript discusses writing code for linear and binary search using arrays in vs code.', 'duration': 31.762, 'max_score': 2474.106, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x82474106.jpg'}, {'end': 2760.434, 'src': 'embed', 'start': 2726.635, 'weight': 2, 'content': [{'end': 2729.458, 'text': "Right now, I'm using just an array of integers.", 'start': 2726.635, 'duration': 2.823}, {'end': 2732.682, 'text': 'Let me go ahead and introduce maybe an array of strings.', 'start': 2729.799, 'duration': 2.883}, {'end': 2733.903, 'text': 'strings instead.', 'start': 2732.722, 'duration': 1.181}, {'end': 2738.905, 'text': "And maybe this time, I'll store a bunch of names and not just integers, but actual strings of names.", 'start': 2733.983, 'duration': 4.922}, {'end': 2741.686, 'text': 'So how might I do this? Well, let me go back to my code here.', 'start': 2738.985, 'duration': 2.701}, {'end': 2746.128, 'text': "I'm going to switch us over to maybe a file called names.c.", 'start': 2742.147, 'duration': 3.981}, {'end': 2749.69, 'text': "And in here, I'll go ahead and include cs50.h.", 'start': 2746.649, 'duration': 3.041}, {'end': 2752.491, 'text': "I'll include standardio.h.", 'start': 2750.25, 'duration': 2.241}, {'end': 2760.434, 'text': "And I'm going to go ahead and, for now, include a new friend from last week, string.h, which gives me some string-related functionality.", 'start': 2753.832, 'duration': 6.602}], 'summary': 'Using arrays of strings to store names in names.c file.', 'duration': 33.799, 'max_score': 2726.635, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x82726635.jpg'}, {'end': 3017.429, 'src': 'embed', 'start': 2991.117, 'weight': 4, 'content': [{'end': 2995.319, 'text': 'So the reason that this function returns an integer and not just a bool,', 'start': 2991.117, 'duration': 4.202}, {'end': 2999.54, 'text': 'true or false is that it actually will allow us to sort these things eventually.', 'start': 2995.319, 'duration': 4.221}, {'end': 3007.003, 'text': "Because if you can tell me if two strings come in this order or in this order or they're the same, you need three possible return values.", 'start': 2999.62, 'duration': 7.383}, {'end': 3008.644, 'text': 'And a bool, of course, only gives you two.', 'start': 3007.043, 'duration': 1.601}, {'end': 3012.145, 'text': 'But an int gives you like 4 billion, even though we just need the three.', 'start': 3009.004, 'duration': 3.141}, {'end': 3017.429, 'text': 'So 0 or a positive number or a negative number is what this function returns.', 'start': 3012.625, 'duration': 4.804}], 'summary': "Function returns int for sorting, providing 3 possible values instead of bool's 2", 'duration': 26.312, 'max_score': 2991.117, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x82991117.jpg'}, {'end': 3109.454, 'src': 'embed', 'start': 3066.337, 'weight': 3, 'content': [{'end': 3074.479, 'text': "And so whereas you can use equals equals for single characters, strcomp, as we'll eventually see, is going to compare multiple characters for us.", 'start': 3066.337, 'duration': 8.142}, {'end': 3075.399, 'text': "There's more logic there.", 'start': 3074.499, 'duration': 0.9}, {'end': 3076.259, 'text': "There's a loop needed.", 'start': 3075.419, 'duration': 0.84}, {'end': 3079.3, 'text': "And that's why it comes with the string library.", 'start': 3076.319, 'duration': 2.981}, {'end': 3082.2, 'text': "But it doesn't just work out of the box with equals equals alone.", 'start': 3079.5, 'duration': 2.7}, {'end': 3086.321, 'text': 'That would literally be comparing two things, not two arrays of things.', 'start': 3082.24, 'duration': 4.081}, {'end': 3089.542, 'text': "And we'll come back to this next week as to what's really going on under the hood.", 'start': 3086.361, 'duration': 3.181}, {'end': 3093.843, 'text': 'So let me go ahead and fix one bug that I just realized I made.', 'start': 3089.922, 'duration': 3.921}, {'end': 3094.963, 'text': 'I want to check.', 'start': 3094.303, 'duration': 0.66}, {'end': 3102.329, 'text': "if the return value of str compare is equal to 0, because per the documentation, that meant they're the same.", 'start': 3095.623, 'duration': 6.706}, {'end': 3105.251, 'text': 'All right, let me go ahead and make names this time.', 'start': 3102.749, 'duration': 2.502}, {'end': 3109.454, 'text': 'Now it compiles, dot slash names, Enter, Found.', 'start': 3105.691, 'duration': 3.763}], 'summary': 'Using strcomp to compare multiple characters, fixing bugs, and achieving successful compilation.', 'duration': 43.117, 'max_score': 3066.337, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x83066337.jpg'}], 'start': 2285.866, 'title': 'Efficient searching and sorting techniques', 'summary': 'Discusses efficient searching and sorting techniques, focusing on the decision-making process between linear search and sorting data, covering use cases, real-world applications, and demonstrating the implementation of linear search in code. additionally, it introduces working with arrays of strings in c, explaining string manipulation and the need for special string comparison functions. furthermore, it delves into string comparison in c programming, emphasizing the need for an integer return value over a bool and demonstrating a linear search implementation for strings using str compare and its return values.', 'chapters': [{'end': 2726.515, 'start': 2285.866, 'title': 'Efficient searching and sorting techniques', 'summary': 'Discusses the decision-making process between linear search and sorting data, highlighting the trade-offs, use cases, and real-world applications, while demonstrating the implementation of linear search in code.', 'duration': 440.649, 'highlights': ['The chapter discusses the decision-making process between linear search and sorting data, highlighting the trade-offs, use cases, and real-world applications The chapter explores the decision-making process between linear search and sorting data, emphasizing the trade-offs involved and the different use cases where each approach may be more suitable. It also provides real-world examples and applications to illustrate the practical implications of these techniques.', 'The implementation of linear search in code is demonstrated, showcasing the iterative approach and error handling The chapter showcases the implementation of linear search in code, demonstrating an iterative approach to searching for a specific value in an array. It also includes error handling techniques, such as returning different values to signify successful or unsuccessful searches.']}, {'end': 2990.597, 'start': 2726.635, 'title': 'Working with arrays of strings in c', 'summary': 'Introduces the concept of working with arrays of strings in c, explaining how to declare and manipulate them, while addressing the need for special string comparison functions due to the lack of a string data type in c.', 'duration': 263.962, 'highlights': ['The chapter introduces the concept of working with arrays of strings in C. It explains how to declare and manipulate arrays of strings.', 'The need for special string comparison functions is addressed due to the lack of a string data type in C. The chapter explains the need to use a special string comparison function like strcomp instead of the equal equals operator when comparing strings in C.']}, {'end': 3376.879, 'start': 2991.117, 'title': 'String comparison and linear search', 'summary': 'Discusses the use of string comparison in c programming, emphasizing the need for an integer return value over a bool, and later demonstrates a linear search implementation for strings, highlighting the use of str compare and its return values.', 'duration': 385.762, 'highlights': ['The function returns an integer instead of a bool to allow for three possible return values, 0, a positive number, or a negative number, which is necessary for comparing strings. The function returns an integer to allow for three possible return values (0, positive number, or negative number) for comparing strings, unlike a bool which only gives two possible values.', 'The use of str compare function for comparing strings is discussed, highlighting its role in comparing multiple characters and the need for a loop for string comparison. The str compare function is used for comparing strings, as it can compare multiple characters and requires a loop for string comparison.', 'Explanation of the interpretation of return values from str compare, where 0 indicates equality and any positive/negative value is interpreted as true, and the use of the inversion operator to check for true or false. The return values from str compare are explained, with 0 indicating equality and any positive/negative value interpreted as true. The use of the inversion operator to check for true or false is also discussed.']}], 'duration': 1091.013, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x82285866.jpg', 'highlights': ['The chapter explores the decision-making process between linear search and sorting data, emphasizing the trade-offs involved and the different use cases where each approach may be more suitable. It also provides real-world examples and applications to illustrate the practical implications of these techniques.', 'The implementation of linear search in code is demonstrated, showcasing the iterative approach and error handling techniques, such as returning different values to signify successful or unsuccessful searches.', 'The chapter introduces the concept of working with arrays of strings in C and explains how to declare and manipulate arrays of strings.', 'The need for special string comparison functions is addressed due to the lack of a string data type in C, explaining the need to use a special string comparison function like strcomp instead of the equal equals operator when comparing strings.', 'The function returns an integer to allow for three possible return values (0, positive number, or negative number) for comparing strings, unlike a bool which only gives two possible values.', 'The str compare function is used for comparing strings, as it can compare multiple characters and requires a loop for string comparison.', 'The return values from str compare are explained, with 0 indicating equality and any positive/negative value interpreted as true. The use of the inversion operator to check for true or false is also discussed.']}, {'end': 4834.302, 'segs': [{'end': 3404.498, 'src': 'embed', 'start': 3377.359, 'weight': 4, 'content': [{'end': 3380.822, 'text': "So now let's actually use this data in some way.", 'start': 3377.359, 'duration': 3.463}, {'end': 3384.164, 'text': "Let's go ahead and actually search for my own name and number here.", 'start': 3380.942, 'duration': 3.222}, {'end': 3387.466, 'text': 'So let me do for int i gets 0.', 'start': 3384.244, 'duration': 3.222}, {'end': 3389.988, 'text': "There's two of us this time, so i less than 2.", 'start': 3387.466, 'duration': 2.522}, {'end': 3391.649, 'text': 'And then i plus plus as before.', 'start': 3389.988, 'duration': 1.661}, {'end': 3394.391, 'text': "And now I'm going to practice what I preached earlier.", 'start': 3392.21, 'duration': 2.181}, {'end': 3398.174, 'text': "And I'm going to use str compare to find my name in this case.", 'start': 3394.471, 'duration': 3.703}, {'end': 3404.498, 'text': "And I'm going to say if str comp of names bracket i equals quote unquote David.", 'start': 3398.514, 'duration': 5.984}], 'summary': "Using str compare to search for 'david' in the names array.", 'duration': 27.139, 'max_score': 3377.359, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x83377359.jpg'}, {'end': 3794.3, 'src': 'heatmap', 'start': 3620.308, 'weight': 0.829, 'content': [{'end': 3629.633, 'text': "that if we want to define a person, wouldn't it be nice if we could have a person data type and then we could have an array called people,", 'start': 3620.308, 'duration': 9.325}, {'end': 3634.795, 'text': 'and maybe that array is our only array, with two things in it, two persons in it.', 'start': 3629.633, 'duration': 5.162}, {'end': 3641.138, 'text': 'But somehow those data types, these persons, would have both a name and a number associated with them.', 'start': 3635.376, 'duration': 5.762}, {'end': 3642.519, 'text': "So we don't need two separate arrays.", 'start': 3641.198, 'duration': 1.321}, {'end': 3643.78, 'text': 'We need one array.', 'start': 3642.759, 'duration': 1.021}, {'end': 3646.761, 'text': 'of persons, a brand new data type.', 'start': 3644.62, 'duration': 2.141}, {'end': 3648.442, 'text': 'So how might we do this?', 'start': 3647.301, 'duration': 1.141}, {'end': 3656.305, 'text': 'Well, if we want every person in the world or in this program to have a name and a number, we literally write out first those two data types.', 'start': 3648.862, 'duration': 7.443}, {'end': 3660.447, 'text': 'Give me a string called name, give me a string called number, semicolon after each.', 'start': 3656.345, 'duration': 4.102}, {'end': 3666.612, 'text': 'And then we wrap those two lines of code with this syntax, which at first glance is a little cryptic.', 'start': 3661.027, 'duration': 5.585}, {'end': 3668.114, 'text': "It's a lot of words all of a sudden.", 'start': 3666.732, 'duration': 1.382}, {'end': 3672.538, 'text': 'But typedef is a new keyword today that defines a new data type.', 'start': 3668.574, 'duration': 3.964}, {'end': 3677.663, 'text': 'This is the C keyword that lets you create your own data type for the very first time.', 'start': 3672.718, 'duration': 4.945}, {'end': 3684.448, 'text': "Struct is another related keyword that tells the compiler that this isn't just a simple data type,", 'start': 3678.363, 'duration': 6.085}, {'end': 3687.009, 'text': 'like an int or a float renamed or something like that.', 'start': 3684.448, 'duration': 2.561}, {'end': 3688.671, 'text': 'It actually is a structure.', 'start': 3687.41, 'duration': 1.261}, {'end': 3694.395, 'text': "It's got some dimensions to it, like two things in it or three things in it or even 50 things inside of it.", 'start': 3688.891, 'duration': 5.504}, {'end': 3699.191, 'text': 'The last word down here is the name that you want to give your data type.', 'start': 3695.37, 'duration': 3.821}, {'end': 3701.632, 'text': 'And it weirdly goes after the curly braces.', 'start': 3699.311, 'duration': 2.321}, {'end': 3705.472, 'text': 'But this is how you invent a data type called person.', 'start': 3702.112, 'duration': 3.36}, {'end': 3713.735, 'text': 'And what this code is implying is that henceforth, the compiler clang will know that a person is composed of a name.', 'start': 3705.933, 'duration': 7.802}, {'end': 3716.375, 'text': "that's a string, and a number, that's a string.", 'start': 3713.735, 'duration': 2.64}, {'end': 3719.676, 'text': "And you don't have to worry about having multiple arrays now.", 'start': 3716.975, 'duration': 2.701}, {'end': 3723.157, 'text': 'You can just have an array of people moving forward.', 'start': 3719.756, 'duration': 3.401}, {'end': 3729.119, 'text': 'So how can we go about using this? Well, let me go back to my code from before where I was implementing a phone book.', 'start': 3723.977, 'duration': 5.142}, {'end': 3733.981, 'text': "And why don't we enhance the phone book code a little bit by borrowing some of that new syntax?", 'start': 3729.379, 'duration': 4.602}, {'end': 3737.782, 'text': 'Let me go to the top of my program above main and define a type,', 'start': 3734.301, 'duration': 3.481}, {'end': 3744.345, 'text': "that's a structure or a data structure that has a name inside of it and that has a number inside of it.", 'start': 3737.782, 'duration': 6.563}, {'end': 3747.366, 'text': 'And the name of this new structure, again, is going to be called person.', 'start': 3744.405, 'duration': 2.961}, {'end': 3753.16, 'text': 'Inside of my code now, let me go ahead and delete this old stuff temporarily.', 'start': 3748.357, 'duration': 4.803}, {'end': 3757.663, 'text': 'Let me give myself an array called people of size 2.', 'start': 3753.701, 'duration': 3.962}, {'end': 3761.246, 'text': "And I'm going to use the non-terse way to do this.", 'start': 3757.663, 'duration': 3.583}, {'end': 3762.347, 'text': "I'm not going to use the curly braces.", 'start': 3761.266, 'duration': 1.081}, {'end': 3767.39, 'text': "I'm going to more pedantically spell out what I want in this array of size 2.", 'start': 3762.387, 'duration': 5.003}, {'end': 3772.816, 'text': 'At location 0,, which is the first person in an array because you always start counting at 0,.', 'start': 3767.39, 'duration': 5.426}, {'end': 3776.24, 'text': "I'm going to give that person a name of quote, unquote Carter.", 'start': 3772.816, 'duration': 3.424}, {'end': 3779.724, 'text': 'And the dot is admittedly one new piece of syntax today too.', 'start': 3776.68, 'duration': 3.044}, {'end': 3785.75, 'text': 'The dot means go inside of that structure and access the variable called name and give it this value Carter.', 'start': 3780.064, 'duration': 5.686}, {'end': 3794.24, 'text': 'Similarly, if I want to give Carter a number, I can go into people bracket 0, dot number and give that the same thing as before, plus 1, 617, 495,', 'start': 3786.391, 'duration': 7.849}, {'end': 3794.3, 'text': '1,000..', 'start': 3794.24, 'duration': 0.06}], 'summary': "Creating a new data type 'person' with name and number fields, enabling an array of people to be used in a program.", 'duration': 173.992, 'max_score': 3620.308, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x83620308.jpg'}, {'end': 3699.191, 'src': 'embed', 'start': 3666.732, 'weight': 1, 'content': [{'end': 3668.114, 'text': "It's a lot of words all of a sudden.", 'start': 3666.732, 'duration': 1.382}, {'end': 3672.538, 'text': 'But typedef is a new keyword today that defines a new data type.', 'start': 3668.574, 'duration': 3.964}, {'end': 3677.663, 'text': 'This is the C keyword that lets you create your own data type for the very first time.', 'start': 3672.718, 'duration': 4.945}, {'end': 3684.448, 'text': "Struct is another related keyword that tells the compiler that this isn't just a simple data type,", 'start': 3678.363, 'duration': 6.085}, {'end': 3687.009, 'text': 'like an int or a float renamed or something like that.', 'start': 3684.448, 'duration': 2.561}, {'end': 3688.671, 'text': 'It actually is a structure.', 'start': 3687.41, 'duration': 1.261}, {'end': 3694.395, 'text': "It's got some dimensions to it, like two things in it or three things in it or even 50 things inside of it.", 'start': 3688.891, 'duration': 5.504}, {'end': 3699.191, 'text': 'The last word down here is the name that you want to give your data type.', 'start': 3695.37, 'duration': 3.821}], 'summary': 'Typedef is a new keyword in c for creating custom data types, like structures with multiple dimensions.', 'duration': 32.459, 'max_score': 3666.732, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x83666732.jpg'}, {'end': 4026.211, 'src': 'embed', 'start': 4000.015, 'weight': 0, 'content': [{'end': 4007.7, 'text': 'But we now have the way in code to express most any type of data that we might want to implement or discuss ultimately.', 'start': 4000.015, 'duration': 7.685}, {'end': 4018.306, 'text': 'So any questions now on struct or defining our own types, the purposes for which are to use arrays, but use them more responsibly now,', 'start': 4008.36, 'duration': 9.946}, {'end': 4025.27, 'text': 'in a better design, but also to lay the foundation for implementing cooler and cooler stuff per our week.', 'start': 4018.306, 'duration': 6.964}, {'end': 4026.211, 'text': '0 discussion? Yeah.', 'start': 4025.27, 'duration': 0.941}], 'summary': 'Coding allows expression of various data types, enabling better array usage and foundation for advanced implementations.', 'duration': 26.196, 'max_score': 4000.015, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x84000015.jpg'}, {'end': 4374.88, 'src': 'embed', 'start': 4353.45, 'weight': 7, 'content': [{'end': 4364.235, 'text': "let's actually take a step back and consider how we might now solve one of the original problems by actually sorting the information we're given in advance and considering,", 'start': 4353.45, 'duration': 10.785}, {'end': 4371.097, 'text': 'per our discussion earlier, just how costly, how time consuming is that? Because that might tip the scales in favor of sorting then searching.', 'start': 4364.235, 'duration': 6.862}, {'end': 4374.88, 'text': 'or maybe just not sorting and only searching.', 'start': 4372.498, 'duration': 2.382}], 'summary': 'Consider sorting information to reduce time and costs for problem-solving.', 'duration': 21.43, 'max_score': 4353.45, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x84353450.jpg'}, {'end': 4512.847, 'src': 'embed', 'start': 4486.633, 'weight': 3, 'content': [{'end': 4490.975, 'text': 'Give us just a moment to finish getting the attire ready.', 'start': 4486.633, 'duration': 4.342}, {'end': 4493.737, 'text': "They're being handed a shirt and a number.", 'start': 4491.316, 'duration': 2.421}, {'end': 4502.662, 'text': 'And let me ask the audience for just a moment, as we have these numbers up here on the screen, these numbers, too, are unsorted.', 'start': 4496.178, 'duration': 6.484}, {'end': 4504.043, 'text': "They're just in random order.", 'start': 4502.702, 'duration': 1.341}, {'end': 4509.526, 'text': 'And let me ask the audience how would you go about sorting these eight numbers on the screen?', 'start': 4504.343, 'duration': 5.183}, {'end': 4512.847, 'text': 'How would you go about sorting these?', 'start': 4511.046, 'duration': 1.801}], 'summary': 'Audience asked to sort 8 unsorted numbers on screen.', 'duration': 26.214, 'max_score': 4486.633, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x84486633.jpg'}], 'start': 3377.359, 'title': 'Implementing custom data types and sorting algorithms', 'summary': 'Covers implementing a phone book using arrays in c, introducing custom data types and structs, discussing the limitations of arrays, and demonstrating sorting algorithms using 8 volunteers to showcase efficiency and human intuition in algorithm design.', 'chapters': [{'end': 3666.612, 'start': 3377.359, 'title': 'Implementing a phone book with arrays', 'summary': 'Covers implementing a phone book using arrays in c, searching for a specific name and printing its corresponding number, then discussing the limitations of using arrays and introducing the concept of a custom data type to more tightly couple data elements.', 'duration': 289.253, 'highlights': ['Introducing a custom data type to tightly couple data elements and eliminate the vulnerabilities of using separate arrays The chapter discusses the limitations of using separate arrays for names and numbers and proposes the introduction of a custom data type, person, to tightly couple the name and number, thus eliminating vulnerabilities and potential mistakes.', 'Searching for a specific name and printing its corresponding number using arrays The chapter demonstrates the process of searching for a specific name and printing its corresponding number using arrays, providing a practical example of implementing a phone book in C.', 'Discussing the limitations of using arrays for a phone book and the potential for mistakes and vulnerabilities The chapter explores the vulnerabilities and potential mistakes that arise from using separate arrays for names and numbers in a phone book, highlighting the lack of a tight relationship between the data elements and the risks associated with program scalability and collaboration.']}, {'end': 3950.193, 'start': 3666.732, 'title': 'Defining custom data types in c', 'summary': "Introduces the typedef and struct keywords in c, explaining how to define custom data types, such as the 'person' structure, and demonstrates their usage in enhancing a phone book program by creating an array of people with names and numbers.", 'duration': 283.461, 'highlights': ["The chapter introduces the typedef and struct keywords in C. The transcript discusses the new keyword 'typedef' that defines a new data type and explains the 'struct' keyword, which is used to define a structure with multiple dimensions and creates a new data type called 'person'.", "Demonstrates how to define a custom data type, such as the 'person' structure. The speaker explains the process of defining a new data type 'person' using the 'struct' keyword, indicating that a person is composed of a name and a number, and demonstrates how to create an array of 'people' with names and numbers.", "Illustrates the usage of custom data types in enhancing a phone book program. The transcript showcases how the custom data types, specifically the 'person' structure, are utilized to enhance a phone book program by creating an array of 'people' with names and numbers, ensuring a better design and encapsulation of related pieces of information."]}, {'end': 4432.054, 'start': 3950.533, 'title': 'Structs and data types in c', 'summary': 'Introduces the concept of structs in c, highlighting their ability to define custom data types for storing different types of data, such as colors, music, and financial numbers, to address limitations of built-in data types. it also discusses the challenges of storing non-numeric data in programming and the importance of considering the efficiency of sorting algorithms.', 'duration': 481.521, 'highlights': ['The chapter introduces the concept of structs in C and their ability to define custom data types for storing different types of data. It discusses the representation of pixels using RGB values and the potential for creating custom data types for music and financial numbers, demonstrating the versatility of structs in C.', 'The discussion addresses the challenges of storing non-numeric data in programming by using strings and the example of storing zip codes. It explains the limitations of storing non-numeric data in built-in data types and the use of strings to accommodate punctuation and leading zeros in data like zip codes.', 'The chapter explores the importance of considering the efficiency of sorting algorithms for organizing data and highlights the trade-offs between sorting and searching. It outlines the problem of sorting unsorted input and the desire to obtain sorted output, providing a concrete example of sorting numbers and hinting at the use of algorithms to accomplish this task.']}, {'end': 4834.302, 'start': 4432.074, 'title': 'Sorting algorithm demonstration', 'summary': 'Features a live demonstration of sorting algorithms using 8 volunteers, showcasing the process of sorting unsorted integers and discussing the efficiency of different approaches, emphasizing the use of step-by-step instructions and human intuition in algorithm design.', 'duration': 402.228, 'highlights': ['The chapter features a live demonstration of sorting algorithms using 8 volunteers The demonstration involves 8 volunteers representing unsorted integers and showcases the sorting process.', 'Discussing the efficiency of different sorting approaches and the use of step-by-step instructions and human intuition in algorithm design The discussion emphasizes the importance of using step-by-step instructions and human intuition in designing efficient sorting algorithms.', 'Emphasizing the process of sorting unsorted integers The chapter focuses on the process of sorting unsorted integers using various approaches and strategies.']}], 'duration': 1456.943, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x83377359.jpg', 'highlights': ['Introducing a custom data type to tightly couple data elements and eliminate the vulnerabilities of using separate arrays', 'The chapter introduces the typedef and struct keywords in C', 'The chapter introduces the concept of structs in C and their ability to define custom data types for storing different types of data', 'The chapter features a live demonstration of sorting algorithms using 8 volunteers', 'Searching for a specific name and printing its corresponding number using arrays', 'The chapter demonstrates the process of searching for a specific name and printing its corresponding number using arrays', 'The chapter introduces the concept of structs in C and their ability to define custom data types for storing different types of data', 'The chapter explores the importance of considering the efficiency of sorting algorithms for organizing data and highlights the trade-offs between sorting and searching']}, {'end': 5560.349, 'segs': [{'end': 4863.064, 'src': 'embed', 'start': 4834.302, 'weight': 2, 'content': [{'end': 4838.004, 'text': "So, if you want to go ahead and exchange places with each other, notice what's just happened.", 'start': 4834.302, 'duration': 3.702}, {'end': 4841.246, 'text': "The problem I'm trying to solve has gotten smaller.", 'start': 4838.264, 'duration': 2.982}, {'end': 4844.088, 'text': "Instead of being size 8, now it's size 7.", 'start': 4841.306, 'duration': 2.782}, {'end': 4846.97, 'text': 'Now granted, I moved 5 to another wrong location.', 'start': 4844.088, 'duration': 2.882}, {'end': 4852.454, 'text': "But if these numbers started off randomly, it doesn't really matter where 5 goes until we get him into the right place.", 'start': 4847.05, 'duration': 5.404}, {'end': 4853.815, 'text': "So I think we've improved.", 'start': 4852.774, 'duration': 1.041}, {'end': 4857.179, 'text': 'And now, if I go back, my loop is sort of coming back around.', 'start': 4854.095, 'duration': 3.084}, {'end': 4863.064, 'text': "I can ignore Celeste and make this a seven step problem and not eight, because I know she's in the right place.", 'start': 4857.559, 'duration': 5.505}], 'summary': 'By exchanging places, the problem size decreased from 8 to 7, showing an improvement in solving the problem.', 'duration': 28.762, 'max_score': 4834.302, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x84834302.jpg'}, {'end': 4905.642, 'src': 'embed', 'start': 4878.194, 'weight': 3, 'content': [{'end': 4882.575, 'text': "I can't sort of optimize as a human and just say number one, let's get you into the right place.", 'start': 4878.194, 'duration': 4.381}, {'end': 4884.416, 'text': "I'd still want to check the whole array.", 'start': 4882.655, 'duration': 1.761}, {'end': 4888.777, 'text': "Why? Yeah? Perhaps there's a number one.", 'start': 4884.436, 'duration': 4.341}, {'end': 4891.798, 'text': "DAVID MALAN, Maybe there's another one, and that could be another problem altogether.", 'start': 4888.797, 'duration': 3.001}, {'end': 4893.598, 'text': 'Other thoughts? Yeah? There could be another zero.', 'start': 4891.938, 'duration': 1.66}, {'end': 4896.179, 'text': 'DAVID MALAN, There could be another zero, indeed.', 'start': 4893.618, 'duration': 2.561}, {'end': 4899.92, 'text': "But I did go through the list once, right? And I kind of know there isn't.", 'start': 4896.219, 'duration': 3.701}, {'end': 4903.041, 'text': "Your thoughts? We don't know that every value is represented.", 'start': 4899.94, 'duration': 3.101}, {'end': 4905.642, 'text': "So maybe there's a half.", 'start': 4903.061, 'duration': 2.581}], 'summary': 'David malan discusses checking arrays for values and potential problems.', 'duration': 27.448, 'max_score': 4878.194, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x84878194.jpg'}, {'end': 5248.931, 'src': 'embed', 'start': 5213.584, 'weight': 1, 'content': [{'end': 5217.625, 'text': 'putting Celeste into the right place and then continuing with everyone else.', 'start': 5213.584, 'duration': 4.041}, {'end': 5223.427, 'text': "So selection sort, as it's formally called, can be described, for instance, with this pseudocode here.", 'start': 5218.185, 'duration': 5.242}, {'end': 5226.91, 'text': 'for i from 0 to n minus 1.', 'start': 5224.167, 'duration': 2.743}, {'end': 5230.213, 'text': 'And again, why this? This is just how we think about talk about arrays.', 'start': 5226.91, 'duration': 3.303}, {'end': 5232.055, 'text': 'The left end is 0.', 'start': 5230.413, 'duration': 1.642}, {'end': 5236.439, 'text': 'The right end is n minus 1, where in this case, n happened to be 8 people.', 'start': 5232.055, 'duration': 4.384}, {'end': 5238.901, 'text': "So that's 0 through 7.", 'start': 5236.819, 'duration': 2.082}, {'end': 5248.931, 'text': 'So for i from 0 to n minus 1, what did I do? I found the smallest number between numbers bracket i and numbers bracket n minus 1.', 'start': 5238.901, 'duration': 10.03}], 'summary': "Using selection sort algorithm to sort 8 people's numbers in an array.", 'duration': 35.347, 'max_score': 5213.584, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x85213584.jpg'}, {'end': 5314.468, 'src': 'embed', 'start': 5288.095, 'weight': 4, 'content': [{'end': 5293.101, 'text': "And that's the technical way of saying, now find the smallest element among the seven remaining volunteers.", 'start': 5288.095, 'duration': 5.006}, {'end': 5297.422, 'text': 'ignoring Celeste this time because she was already in the correct location.', 'start': 5293.881, 'duration': 3.541}, {'end': 5300.063, 'text': 'So the problem went from size 8 to size 7.', 'start': 5297.442, 'duration': 2.621}, {'end': 5305.445, 'text': "And if we repeat size 6, 5, 4, 3, 2, 1 until boom, it's all done at the very end.", 'start': 5300.063, 'duration': 5.382}, {'end': 5310.627, 'text': 'So this is just one way of expressing in pseudocode what we did a little more organically,', 'start': 5305.805, 'duration': 4.822}, {'end': 5314.468, 'text': 'in a formalization of what someone volunteered out in the audience.', 'start': 5310.627, 'duration': 3.841}], 'summary': 'Using pseudocode, the problem reduced from size 8 to 7 volunteers, and continued decreasing until it was solved at the end.', 'duration': 26.373, 'max_score': 5288.095, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x85288095.jpg'}, {'end': 5560.349, 'src': 'embed', 'start': 5512.462, 'weight': 0, 'content': [{'end': 5521.83, 'text': 'if we look at that highest order term, to get a sense of what the algorithm feels like, if you will, or what it even looks like graphically.', 'start': 5512.462, 'duration': 9.368}, {'end': 5530.937, 'text': 'All right, so with that said, we might describe bubble sort as being in big O, sorry, selection sort as being in big O of n squared.', 'start': 5522.59, 'duration': 8.347}, {'end': 5538.303, 'text': 'But what, if we consider now the best case scenario, an opportunity to talk about a lower bound?', 'start': 5531.757, 'duration': 6.546}, {'end': 5543.338, 'text': 'In the best case, how many steps does selection sort take??', 'start': 5539.235, 'duration': 4.103}, {'end': 5544.599, 'text': 'Well, here we need some context.', 'start': 5543.358, 'duration': 1.241}, {'end': 5548.201, 'text': 'Like, what does it mean to be the best case or the worst case when it comes to sorting?', 'start': 5544.639, 'duration': 3.562}, {'end': 5553.845, 'text': "Like, what could you imagine meaning the best possible scenario when you're trying to sort a bunch of numbers?", 'start': 5549.182, 'duration': 4.663}, {'end': 5557.007, 'text': 'OK, the whole crew here again.', 'start': 5555.826, 'duration': 1.181}, {'end': 5560.349, 'text': "Yeah, All right, they're already sorted right?", 'start': 5557.067, 'duration': 3.282}], 'summary': 'Selection sort in best case takes o(n) steps.', 'duration': 47.887, 'max_score': 5512.462, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x85512462.jpg'}], 'start': 4834.302, 'title': 'Sorting algorithms', 'summary': 'Discusses the sorting numbers algorithm, emphasizing the process of reducing problem size and optimizing array placement. it also covers the selection sort algorithm, analyzing its efficiency with a time complexity of o(n^2).', 'chapters': [{'end': 4896.179, 'start': 4834.302, 'title': 'Sorting numbers algorithm', 'summary': 'Discusses a sorting algorithm, demonstrating the process of exchanging numbers to reduce the problem size, and the importance of thoroughly checking and optimizing the array to ensure correct placement, with a focus on identifying the smallest numbers. the problem initially had size 8, which was reduced to size 7 after the exchange, and the speaker aims to further optimize the process by identifying the smallest numbers in the array.', 'duration': 61.877, 'highlights': ['The problem size was reduced from 8 to 7 after exchanging numbers, demonstrating the effectiveness of the algorithm.', 'The importance of thoroughly checking the entire array is emphasized, as the presence of duplicates or misplaced numbers could lead to additional problems.', 'The speaker focuses on identifying the smallest numbers in the array to optimize the sorting process and ensure correct placement.']}, {'end': 5560.349, 'start': 4896.219, 'title': 'Selection sort algorithm', 'summary': 'Discusses the selection sort algorithm, where the process of sorting was demonstrated using volunteers and later formalized into pseudocode, and its efficiency was analyzed with a focus on its running time, resulting in the conclusion that it has a time complexity of o(n^2).', 'duration': 664.13, 'highlights': ['The process of sorting was demonstrated using volunteers and later formalized into pseudocode. The speaker demonstrated the process of sorting using volunteers and then formalized it into pseudocode, providing a clear explanation of the selection sort algorithm.', 'The efficiency of the selection sort algorithm was analyzed, resulting in the conclusion that it has a time complexity of O(n^2). The speaker analyzed the efficiency of the selection sort algorithm and concluded that its running time complexity is O(n^2), explaining the steps involved in reaching this conclusion.', 'Discussion on the best case scenario of the selection sort algorithm was initiated. The speaker initiated a discussion on the best case scenario for the selection sort algorithm, prompting the audience to consider the best possible scenario when sorting a set of numbers.']}], 'duration': 726.047, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x84834302.jpg', 'highlights': ['The efficiency of the selection sort algorithm was analyzed, resulting in the conclusion that it has a time complexity of O(n^2).', 'The speaker demonstrated the process of sorting using volunteers and then formalized it into pseudocode, providing a clear explanation of the selection sort algorithm.', 'The problem size was reduced from 8 to 7 after exchanging numbers, demonstrating the effectiveness of the algorithm.', 'The importance of thoroughly checking the entire array is emphasized, as the presence of duplicates or misplaced numbers could lead to additional problems.', 'The speaker focuses on identifying the smallest numbers in the array to optimize the sorting process and ensure correct placement.', 'Discussion on the best case scenario of the selection sort algorithm was initiated.']}, {'end': 6119.881, 'segs': [{'end': 5658.171, 'src': 'embed', 'start': 5631.76, 'weight': 0, 'content': [{'end': 5638.843, 'text': 'So in this case, yes, I would claim that the omega notation for selection sort is also big O of n squared.', 'start': 5631.76, 'duration': 7.083}, {'end': 5640.344, 'text': 'So those are the kinds of numbers to beat.', 'start': 5638.923, 'duration': 1.421}, {'end': 5645.847, 'text': 'It seems like the upper bound and lower bound of selection sort are indeed n squared.', 'start': 5640.704, 'duration': 5.143}, {'end': 5649.728, 'text': 'And so we can also describe selection sort, therefore, as being in theta of n squared.', 'start': 5646.247, 'duration': 3.481}, {'end': 5654.33, 'text': "That's the first algorithm we've had the chance to describe that in, which is to say that it's kind of slow.", 'start': 5649.748, 'duration': 4.582}, {'end': 5658.171, 'text': "I mean, maybe other algorithms are slower, but this isn't the best starting point.", 'start': 5654.79, 'duration': 3.381}], 'summary': 'Selection sort has a time complexity of o(n^2) and is considered slow.', 'duration': 26.411, 'max_score': 5631.76, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x85631760.jpg'}, {'end': 5688.275, 'src': 'embed', 'start': 5662.913, 'weight': 2, 'content': [{'end': 5668.395, 'text': 'Even though you verbally propose them in a different order, this second algorithm we did is generally known as bubble sort.', 'start': 5662.913, 'duration': 5.482}, {'end': 5674.377, 'text': 'And I deliberately used that word a bit ago, saying the big values are bubbling their way up to the right.', 'start': 5668.675, 'duration': 5.702}, {'end': 5678.502, 'text': 'to kind of capture the fact that, indeed, this algorithm works differently.', 'start': 5675.057, 'duration': 3.445}, {'end': 5680.605, 'text': "But let's consider if it's better or worse.", 'start': 5678.602, 'duration': 2.003}, {'end': 5683.729, 'text': 'So here we have pseudocode for bubble sort.', 'start': 5681.005, 'duration': 2.724}, {'end': 5685.511, 'text': 'You could write this too in different ways.', 'start': 5684.049, 'duration': 1.462}, {'end': 5688.275, 'text': "But let's consider what we did on the stage.", 'start': 5685.992, 'duration': 2.283}], 'summary': "The second algorithm discussed is bubble sort, working differently than others. consider if it's better or worse.", 'duration': 25.362, 'max_score': 5662.913, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x85662913.jpg'}, {'end': 5844.883, 'src': 'embed', 'start': 5817.675, 'weight': 1, 'content': [{'end': 5824.376, 'text': 'And so how might we quantify the running time of this algorithm? Well, one way to see it is to just literally look at the pseudocode.', 'start': 5817.675, 'duration': 6.701}, {'end': 5828.377, 'text': 'The outer loop repeats n minus 1 times.', 'start': 5824.817, 'duration': 3.56}, {'end': 5830.098, 'text': 'By definition, it literally says that.', 'start': 5828.457, 'duration': 1.641}, {'end': 5835.499, 'text': 'The inner loop, the for loop, also iterates n minus 1 times.', 'start': 5830.638, 'duration': 4.861}, {'end': 5838.519, 'text': "Why? Because it's going from 0 to n minus 2.", 'start': 5836.159, 'duration': 2.36}, {'end': 5844.883, 'text': "And if that's hard to think about, that's the same thing as 1 to n minus 1 if you just add 1 to both ends of the formula.", 'start': 5838.519, 'duration': 6.364}], 'summary': "The algorithm's running time is quantified by the outer loop repeating n minus 1 times and the inner loop also iterating n minus 1 times.", 'duration': 27.208, 'max_score': 5817.675, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x85817675.jpg'}], 'start': 5560.389, 'title': 'Sorting and analyzing algorithms', 'summary': 'Delves into the inefficiencies of selection sort, introduces bubble sort as an alternative with insights on complexities and differences, details the bubble sort algorithm, its inner and outer loops, running time analysis, best case scenario, and optimizations for shorter execution, concluding with a comparison to selection sort and a consideration for future improvements.', 'chapters': [{'end': 5709.482, 'start': 5560.389, 'title': 'Sorting algorithms and their efficiencies', 'summary': 'Discusses the inefficiencies of selection sort and introduces bubble sort as a potentially better alternative, providing insights on their complexities and differences.', 'duration': 149.093, 'highlights': ["Selection sort's inefficiency is demonstrated through its inability to leverage pre-sorted data, resulting in a lower bound omega notation of n squared.", 'Bubble sort is introduced as a potential improvement, with a focus on its different approach and considerations for its efficiency compared to selection sort.']}, {'end': 6119.881, 'start': 5710.263, 'title': 'Bubble sort algorithm analysis', 'summary': 'Details the bubble sort algorithm, explaining its inner and outer loops, running time analysis, best case scenario, and an optimization to shorten its execution, concluding with a comparison to selection sort and a consideration for future improvements.', 'duration': 409.618, 'highlights': ['The outer loop of the bubble sort algorithm repeats n minus 1 times, and the inner for loop also iterates n minus 1 times, resulting in a time complexity of n minus 1 squared, which simplifies to n squared as n gets large.', 'In the best case scenario, when the list is already sorted, an optimization in the pseudocode allows the algorithm to short circuit the inefficient looping, resulting in an omega notation for bubble sort of omega of n, improving its efficiency in such scenarios.', "The chapter also addresses a comparison between selection sort and bubble sort, where the latter's omega notation being better than the former suggests its potential usefulness in best case scenarios, but the goal is to improve upon both algorithms in the future."]}], 'duration': 559.492, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x85560389.jpg', 'highlights': ["Bubble sort's omega notation of n is an optimization for pre-sorted data.", "Bubble sort's outer loop repeats n-1 times, inner loop iterates n-1 times.", "Selection sort's inefficiency is demonstrated through its inability to leverage pre-sorted data."]}, {'end': 7046.732, 'segs': [{'end': 6150.038, 'src': 'embed', 'start': 6119.881, 'weight': 0, 'content': [{'end': 6124.885, 'text': 'so that when n gets really large, which of these choices is going to matter the most?', 'start': 6119.881, 'duration': 5.004}, {'end': 6131.008, 'text': "At the end of the day, it's actually perfectly reasonable to use selection sort or bubble sort if you don't have that much data,", 'start': 6125.265, 'duration': 5.743}, {'end': 6132.169, 'text': "because they're going to be pretty fast.", 'start': 6131.008, 'duration': 1.161}, {'end': 6138.131, 'text': 'My god, our computers nowadays are 1 gigahertz, 2 gigahertz, 1 billion things per second, 2 billion things per second.', 'start': 6132.189, 'duration': 5.942}, {'end': 6143.514, 'text': 'But if we have large data sets, as we will later in the term and as you might in the real world, at the Googles of the world,', 'start': 6138.452, 'duration': 5.062}, {'end': 6145.475, 'text': "then you're going to want to be more thoughtful.", 'start': 6143.514, 'duration': 1.961}, {'end': 6146.656, 'text': "And that's where we're going today.", 'start': 6145.495, 'duration': 1.161}, {'end': 6150.038, 'text': "All right, so let's actually see this visualized a little bit.", 'start': 6147.296, 'duration': 2.742}], 'summary': 'Efficiency of sorting algorithms becomes critical for large data sets, as modern computers process billions of items per second.', 'duration': 30.157, 'max_score': 6119.881, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x86119881.jpg'}, {'end': 6353.909, 'src': 'embed', 'start': 6322.534, 'weight': 3, 'content': [{'end': 6328.517, 'text': 'So the challenge at hand is to do better than selection sort and better than bubble sort.', 'start': 6322.534, 'duration': 5.983}, {'end': 6332.398, 'text': 'And ideally, not just marginally better, but fundamentally better.', 'start': 6328.577, 'duration': 3.821}, {'end': 6338.681, 'text': 'Just like in week 0, that third and final divide and conquer algorithm was sort of fundamentally faster than the other two.', 'start': 6332.458, 'duration': 6.223}, {'end': 6345.804, 'text': 'So can we do better than something on the order of n squared? Well, I bet we can if we start to approach the problem a little differently.', 'start': 6338.741, 'duration': 7.063}, {'end': 6349.346, 'text': "The sorts we've done thus far, generally known as comparison sorts,", 'start': 6346.164, 'duration': 3.182}, {'end': 6353.909, 'text': 'and that kind of captures the reality that we were doing a huge number of comparisons again and again.', 'start': 6349.346, 'duration': 4.563}], 'summary': 'Challenge: improve on n squared complexity of comparison sorts', 'duration': 31.375, 'max_score': 6322.534, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x86322534.jpg'}, {'end': 6568.246, 'src': 'embed', 'start': 6542.075, 'weight': 5, 'content': [{'end': 6546.818, 'text': 'Notice. among the benefits of doing this is it kind of tightens the code up, makes it a little more succinct,', 'start': 6542.075, 'duration': 4.743}, {'end': 6548.519, 'text': "even though that's kind of a fringe benefit here.", 'start': 6546.818, 'duration': 1.701}, {'end': 6552.782, 'text': "But it's an elegant way, too, of describing a problem.", 'start': 6549.079, 'duration': 3.703}, {'end': 6560.744, 'text': 'by just having a function use itself to solve a smaller puzzle at hand.', 'start': 6553.402, 'duration': 7.342}, {'end': 6568.246, 'text': "So let's now consider a familiar problem, a smaller version than the one you've dabbled with, this sort of pyramid, this half pyramid from Mario.", 'start': 6561.404, 'duration': 6.842}], 'summary': 'Using recursion tightens code, makes it succinct, and elegantly solves problems, like the half pyramid from mario.', 'duration': 26.171, 'max_score': 6542.075, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x86542075.jpg'}, {'end': 6733.356, 'src': 'embed', 'start': 6704.457, 'weight': 6, 'content': [{'end': 6708.037, 'text': 'So on each row, how many bricks do I want to print??', 'start': 6704.457, 'duration': 3.58}, {'end': 6715.339, 'text': 'Well, I think I want to do this for int j, for instance, common to use j after i, if you have a nested loop.', 'start': 6708.558, 'duration': 6.781}, {'end': 6723.069, 'text': "Let's start j at 0 and do this so long as j is less than i plus 1.", 'start': 6715.839, 'duration': 7.23}, {'end': 6723.85, 'text': 'And then do j++.', 'start': 6723.069, 'duration': 0.781}, {'end': 6730.454, 'text': "So why i plus 1? Well, again, when i equals 0, that's the first row, and I want one brick.", 'start': 6724.07, 'duration': 6.384}, {'end': 6733.356, 'text': "When i equals 1, that's the second row, I want two bricks.", 'start': 6730.734, 'duration': 2.622}], 'summary': 'Using nested loops to print a number of bricks based on row number.', 'duration': 28.899, 'max_score': 6704.457, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x86704457.jpg'}, {'end': 6834.454, 'src': 'heatmap', 'start': 6747.906, 'weight': 0.899, 'content': [{'end': 6752.349, 'text': "I'm going to save the new line for about here instead.", 'start': 6747.906, 'duration': 4.443}, {'end': 6759.313, 'text': "All right, the last thing I'm going to do is copy and paste the prototype at the top of the file so that I can call this.", 'start': 6753.351, 'duration': 5.962}, {'end': 6763.015, 'text': 'And again, this is sort of now week one, week two.', 'start': 6759.733, 'duration': 3.282}, {'end': 6766.776, 'text': "Wouldn't necessarily come to your mind as quickly as it might to mine after all this practice,", 'start': 6763.095, 'duration': 3.681}, {'end': 6772.858, 'text': 'but this is something reminiscent of what you yourselves did already for Mario printing out a pyramid that, hopefully, in a moment,', 'start': 6766.776, 'duration': 6.082}, {'end': 6773.738, 'text': 'is going to look like this', 'start': 6772.858, 'duration': 0.88}, {'end': 6775.959, 'text': 'So let me go back to my code.', 'start': 6774.419, 'duration': 1.54}, {'end': 6777.8, 'text': 'Let me run make iteration.', 'start': 6776.419, 'duration': 1.381}, {'end': 6780.469, 'text': 'And let me do dot slash iteration.', 'start': 6779.008, 'duration': 1.461}, {'end': 6781.931, 'text': "I'll type in 4.", 'start': 6780.509, 'duration': 1.422}, {'end': 6783.852, 'text': 'And voila, seems to be correct.', 'start': 6781.931, 'duration': 1.921}, {'end': 6786.154, 'text': "And let's assume it's going to work for other inputs as well.", 'start': 6783.912, 'duration': 2.242}, {'end': 6787.155, 'text': 'Oh, thank you.', 'start': 6786.635, 'duration': 0.52}, {'end': 6788.336, 'text': 'This is.', 'start': 6787.916, 'duration': 0.42}, {'end': 6796.571, 'text': 'So this is indeed an example of iteration, doing something again and again.', 'start': 6791.886, 'duration': 4.685}, {'end': 6798.092, 'text': "And it's very procedural.", 'start': 6796.591, 'duration': 1.501}, {'end': 6800.855, 'text': 'Like, I literally have a function called draw that does this thing.', 'start': 6798.133, 'duration': 2.722}, {'end': 6806.481, 'text': "But I can think about implementing draw in a somewhat different way that's kind of clever.", 'start': 6801.316, 'duration': 5.165}, {'end': 6810.105, 'text': "And it's not strictly necessary for this problem, because this problem honestly is not.", 'start': 6806.781, 'duration': 3.324}, {'end': 6816.147, 'text': 'that complicated to solve once you have practice under your belt, certainly the first time around, probably significantly challenging.', 'start': 6810.465, 'duration': 5.682}, {'end': 6822.89, 'text': 'But now that you kind of associate, OK, row 1 with one brick, row 2 with two bricks, it kind of comes together with these for loops.', 'start': 6816.207, 'duration': 6.683}, {'end': 6825.391, 'text': 'But how else could we think about this problem?', 'start': 6823.39, 'duration': 2.001}, {'end': 6834.454, 'text': "Well, this physical structure, these bricks, in some sense is a recursive structure, a structure that's defined in terms of itself.", 'start': 6825.771, 'duration': 8.683}], 'summary': 'Demonstration of iteration and procedural programming in code with a recursive structure.', 'duration': 86.548, 'max_score': 6747.906, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x86747906.jpg'}, {'end': 6935.828, 'src': 'embed', 'start': 6904.064, 'weight': 7, 'content': [{'end': 6905.305, 'text': 'And so you can just kind of stop.', 'start': 6904.064, 'duration': 1.241}, {'end': 6907.667, 'text': 'The base case is when there is no more pyramid.', 'start': 6905.385, 'duration': 2.282}, {'end': 6911.57, 'text': "So there's a way to sort of draw a line in the sand and say, stop, no more arguments.", 'start': 6908.067, 'duration': 3.503}, {'end': 6921.957, 'text': 'But this idea of defining a physical structure in terms of itself or code in terms of itself actually lets us do some interesting new algorithms.', 'start': 6912.17, 'duration': 9.787}, {'end': 6923.799, 'text': 'Let me go back to my code here.', 'start': 6922.238, 'duration': 1.561}, {'end': 6935.828, 'text': 'Let me go ahead and create one final file here called recursion.c that leverages this idea of this built-in self-referential nature.', 'start': 6924.279, 'duration': 11.549}], 'summary': 'Using recursion to create self-referential algorithms in code.', 'duration': 31.764, 'max_score': 6904.064, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x86904064.jpg'}], 'start': 6119.881, 'title': 'Sorting algorithms and recursive structures', 'summary': "Discusses the impact of data size on sorting algorithms' efficiency, emphasizing the relevance of selection sort and bubble sort for small data sets. it also explores visualization of sorting algorithms and introduces recursion. additionally, it covers nested loops for printing a pyramid and leverages recursive structures to create a recursive algorithm for drawing the pyramid.", 'chapters': [{'end': 6150.038, 'start': 6119.881, 'title': 'Efficiency of sorting algorithms', 'summary': 'Discusses the impact of data size on the efficiency of sorting algorithms, highlighting the relevance of selection sort and bubble sort for small data sets and the need for more thoughtful approaches for large data sets, particularly in real-world scenarios like at companies such as google, where data sets can be in the billions.', 'duration': 30.157, 'highlights': ['The relevance of selection sort and bubble sort for small data sets is emphasized due to their relatively fast performance.', 'The need for more thoughtful approaches for large data sets is highlighted, particularly in real-world scenarios like at companies such as Google, where data sets can be in the billions.', 'The significant computing power of modern computers is illustrated with examples of speeds reaching 1 gigahertz and 2 gigahertz, equating to 1 billion and 2 billion things per second respectively.']}, {'end': 6703.777, 'start': 6150.078, 'title': 'Visualization of sorting algorithms', 'summary': 'Explores the visualization of selection sort and bubble sort algorithms, demonstrating their n-squared nature and inefficiency, before introducing the concept of recursion to approach the sorting problem fundamentally differently, aiming to achieve fundamentally better performance. it also discusses the use of recursion in the context of search algorithms and its benefits in tightening the code and describing problems more elegantly.', 'duration': 553.699, 'highlights': ['The visualization of selection sort and bubble sort algorithms demonstrates their n-squared nature and inefficiency, with the repetition of steps and retracing of bars, highlighting the need to find a fundamentally better approach. The visualization of selection sort and bubble sort algorithms showcases their n-squared nature and inefficiency, as evidenced by the repetition of steps and retracing of bars, indicating the need for a fundamentally better approach to sorting.', 'The introduction of recursion as a programming technique to approach the sorting problem fundamentally differently, aiming to achieve fundamentally better performance, is discussed, with a comparison to the divide and conquer algorithm from week 0. The introduction of recursion as a programming technique to approach the sorting problem fundamentally differently is discussed, drawing a comparison to the divide and conquer algorithm from week 0 and aiming to achieve fundamentally better performance.', 'The benefits of recursion in tightening the code and describing problems more elegantly are highlighted, with a comparison to the use of recursion in the context of search algorithms. The benefits of recursion in tightening the code and describing problems more elegantly are highlighted, with a comparison to the use of recursion in the context of search algorithms.']}, {'end': 7046.732, 'start': 6704.457, 'title': 'Nested loops and recursive structures', 'summary': 'Covers the implementation of nested loops for printing a pyramid of bricks, with the number of bricks increasing with each row, and then explores the concept of recursive structures and leverages it to create a recursive algorithm for drawing the pyramid.', 'duration': 342.275, 'highlights': ['The chapter covers the implementation of nested loops for printing a pyramid of bricks, with the number of bricks increasing with each row. The speaker explains the use of nested loops to print a pyramid of bricks, where the number of bricks increases with each row, e.g., row 1 with one brick, row 2 with two bricks, etc.', 'The concept of recursive structures is introduced, and the speaker leverages it to create a recursive algorithm for drawing the pyramid. The concept of recursive structures is introduced, and the speaker demonstrates leveraging it to create a recursive algorithm for drawing the pyramid, by defining a pyramid of height n in terms of a pyramid of height n-1 and adding one more row of hashes.']}], 'duration': 926.851, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x86119881.jpg', 'highlights': ['The relevance of selection sort and bubble sort for small data sets is emphasized due to their relatively fast performance.', 'The need for more thoughtful approaches for large data sets is highlighted, particularly in real-world scenarios like at companies such as Google, where data sets can be in the billions.', 'The significant computing power of modern computers is illustrated with examples of speeds reaching 1 gigahertz and 2 gigahertz, equating to 1 billion and 2 billion things per second respectively.', 'The visualization of selection sort and bubble sort algorithms demonstrates their n-squared nature and inefficiency, with the repetition of steps and retracing of bars, highlighting the need to find a fundamentally better approach.', 'The introduction of recursion as a programming technique to approach the sorting problem fundamentally differently, aiming to achieve fundamentally better performance, is discussed, with a comparison to the divide and conquer algorithm from week 0.', 'The benefits of recursion in tightening the code and describing problems more elegantly are highlighted, with a comparison to the use of recursion in the context of search algorithms.', 'The chapter covers the implementation of nested loops for printing a pyramid of bricks, with the number of bricks increasing with each row.', 'The concept of recursive structures is introduced, and the speaker leverages it to create a recursive algorithm for drawing the pyramid.']}, {'end': 8135.597, 'segs': [{'end': 7164.561, 'src': 'embed', 'start': 7136.059, 'weight': 4, 'content': [{'end': 7148.069, 'text': 'But if n equals 1 or 2 or 3 or anything higher, it is reasonable to draw a pyramid of slightly shorter height, like instead of 4, 3,', 'start': 7136.059, 'duration': 12.01}, {'end': 7150.191, 'text': 'and then go ahead and print one more row.', 'start': 7148.069, 'duration': 2.122}, {'end': 7155.896, 'text': 'So this is an example now of code that calls itself within itself.', 'start': 7150.891, 'duration': 5.005}, {'end': 7157.937, 'text': 'Draw is calling draw.', 'start': 7156.596, 'duration': 1.341}, {'end': 7164.561, 'text': "But this so-called base case ensures, this conditional ensures, that we're not going to do this forever.", 'start': 7158.217, 'duration': 6.344}], 'summary': 'The code draws a pyramid recursively, shortening height by 1 each time, to avoid infinite recursion.', 'duration': 28.502, 'max_score': 7136.059, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x87136059.jpg'}, {'end': 7316.369, 'src': 'embed', 'start': 7288.366, 'weight': 2, 'content': [{'end': 7292.169, 'text': 'So here is the pseudocode I proposed for this algorithm called merge sort.', 'start': 7288.366, 'duration': 3.803}, {'end': 7300.676, 'text': 'In the spirit of recursion, this sorting algorithm literally calls itself by using the verb sort in its pseudocode.', 'start': 7292.65, 'duration': 8.026}, {'end': 7302.317, 'text': 'So how does merge, sort, work?', 'start': 7301.056, 'duration': 1.261}, {'end': 7307.281, 'text': 'It sort of obnoxiously says well, if you want to sort all of these things, go sort the left half,', 'start': 7302.818, 'duration': 4.463}, {'end': 7310.204, 'text': 'then go sort the right half and then merge the two together.', 'start': 7307.281, 'duration': 2.923}, {'end': 7311.305, 'text': 'Now obnoxious?', 'start': 7310.444, 'duration': 0.861}, {'end': 7311.785, 'text': 'in what sense?', 'start': 7311.305, 'duration': 0.48}, {'end': 7316.369, 'text': 'Well, if I just asked you to sort something and you just tell me well, go, sort that thing, and then go, sort that thing,', 'start': 7311.825, 'duration': 4.544}], 'summary': 'The merge sort algorithm uses recursion to sort and merge the left and right halves of the array.', 'duration': 28.003, 'max_score': 7288.366, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x87288366.jpg'}, {'end': 7533.754, 'src': 'embed', 'start': 7503.818, 'weight': 1, 'content': [{'end': 7508.26, 'text': "We haven't done the guts of the algorithm yet, sort the left half and sort the right half.", 'start': 7503.818, 'duration': 4.442}, {'end': 7512.881, 'text': 'But I claim that that is how, mechanically, you merge two sorted halves.', 'start': 7508.52, 'duration': 4.361}, {'end': 7516.922, 'text': 'You keep looking at the beginning of each list, and you just kind of weave them together.', 'start': 7512.901, 'duration': 4.021}, {'end': 7520.705, 'text': 'based on which one belongs first based on its size.', 'start': 7517.302, 'duration': 3.403}, {'end': 7528.09, 'text': "So, if you agree that that was a reasonable way to merge two lists together, let's go ahead and focus, lastly,", 'start': 7521.105, 'duration': 6.985}, {'end': 7533.754, 'text': 'on what it means to actually sort the left half and sort the right half of a whole bunch of numbers.', 'start': 7528.09, 'duration': 5.664}], 'summary': 'The algorithm merges two sorted halves by weaving them based on size.', 'duration': 29.936, 'max_score': 7503.818, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x87503818.jpg'}, {'end': 8014.986, 'src': 'embed', 'start': 7984.789, 'weight': 0, 'content': [{'end': 7990.574, 'text': 'The big O notation for merge sort, it turns out, is actually going to be n times log n.', 'start': 7984.789, 'duration': 5.785}, {'end': 7998.299, 'text': "And even if you're a little rusty still on your logarithms, we saw in week 0 And again today, that log n is smaller than n.", 'start': 7990.574, 'duration': 7.725}, {'end': 7999.139, 'text': "That's a good thing.", 'start': 7998.299, 'duration': 0.84}, {'end': 8000.84, 'text': 'Any binary search was log n.', 'start': 7999.239, 'duration': 1.601}, {'end': 8003.421, 'text': "That's faster than linear search, which was n.", 'start': 8000.84, 'duration': 2.581}, {'end': 8008.423, 'text': 'So n times log n is, of course, smaller than n times n, or n squared.', 'start': 8003.421, 'duration': 5.002}, {'end': 8014.986, 'text': "So it's sort of lower on this little cheat sheet that I've been drawing, which is to suggest that its running time is indeed better or faster.", 'start': 8008.924, 'duration': 6.062}], 'summary': "Merge sort's big o notation is n * log n, faster than n squared.", 'duration': 30.197, 'max_score': 7984.789, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x87984789.jpg'}, {'end': 8135.597, 'src': 'heatmap', 'start': 8068.022, 'weight': 3, 'content': [{'end': 8070.044, 'text': 'And you can see it being done half at a time.', 'start': 8068.022, 'duration': 2.022}, {'end': 8073.046, 'text': 'And you see sort of remnants of the previous bars.', 'start': 8070.104, 'duration': 2.942}, {'end': 8075.468, 'text': 'Actually, that was unfair.', 'start': 8073.847, 'duration': 1.621}, {'end': 8076.709, 'text': 'Let me zoom out here.', 'start': 8075.508, 'duration': 1.201}, {'end': 8080.573, 'text': 'Let me zoom out so you can actually see the height here.', 'start': 8077.59, 'duration': 2.983}, {'end': 8084.565, 'text': 'Let me go ahead and randomize this again and run merge sort.', 'start': 8082.062, 'duration': 2.503}, {'end': 8085.146, 'text': 'There we go.', 'start': 8084.726, 'duration': 0.42}, {'end': 8089.432, 'text': 'Now you can see the second array and where the values are going temporarily.', 'start': 8085.186, 'duration': 4.246}, {'end': 8095.76, 'text': 'And even though this one looks way more cryptic visualization-wise, it does seem to be moving faster.', 'start': 8089.452, 'duration': 6.308}, {'end': 8097.983, 'text': 'And it seems to be merging halves together.', 'start': 8096.201, 'duration': 1.782}, {'end': 8099.205, 'text': "And boom, it's done.", 'start': 8098.043, 'duration': 1.162}, {'end': 8103.888, 'text': "Let's actually see, in conclusion, what these algorithms compare to.", 'start': 8099.645, 'duration': 4.243}, {'end': 8110.272, 'text': 'And consider that, moving forward, as we write more and more code, the goal is, again, not just to be correct, but to be well designed.', 'start': 8103.988, 'duration': 6.284}, {'end': 8113.674, 'text': 'And one measure of design is going to, indeed, be efficiency.', 'start': 8110.312, 'duration': 3.362}, {'end': 8122.099, 'text': 'So here we have, in final, a visualization of three algorithms, selection sort, bubble sort, and merge sort, from top to bottom.', 'start': 8113.734, 'duration': 8.365}, {'end': 8125.501, 'text': "And let's see what these algorithms might look or sound like here.", 'start': 8122.439, 'duration': 3.062}, {'end': 8127.803, 'text': 'Ooh, if we can dim the lights for dramatic effect.', 'start': 8125.521, 'duration': 2.282}, {'end': 8135.597, 'text': 'Selections on top, bubble on bottom, merge in the middle.', 'start': 8132.239, 'duration': 3.358}], 'summary': 'Visualization of selection sort, bubble sort, and merge sort algorithms, emphasizing efficiency and comparison.', 'duration': 25.285, 'max_score': 8068.022, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x88068022.jpg'}], 'start': 7047.412, 'title': 'Merge sort algorithm', 'summary': 'Discusses recursion with a base case in a draw function, transition to merge sort sorting algorithm, explaining its concept, process of merging and sorting lists, illustrating with pseudocode and examples, and highlighting efficiency and trade-offs in comparison to other sorting algorithms.', 'chapters': [{'end': 7270.544, 'start': 7047.412, 'title': 'Recursion and base case', 'summary': 'Discusses the concept of recursion with a base case in a draw function, where the base case ensures that the function does not loop forever, preventing potential memory issues and bugs, and then transitions to discussing the merge sort sorting algorithm.', 'duration': 223.132, 'highlights': ['The base case in the draw function ensures that the function does not loop forever, preventing potential memory issues and bugs.', 'The draw function is designed to stop when n equals 1 or 0, preventing infinite loops and potential memory issues.', 'The discussion transitions to the merge sort sorting algorithm, aiming to improve efficiency compared to selection sort and bubble sort.']}, {'end': 7642.429, 'start': 7271.636, 'title': 'Understanding merge sort algorithm', 'summary': 'Explains the merge sort algorithm, illustrating the concept of recursion and the process of merging and sorting lists, culminating in a demonstration of how the merge sort algorithm works with pseudocode and examples of sorting and merging lists.', 'duration': 370.793, 'highlights': ['The chapter explains the concept of recursion and its application in understanding the merge sort algorithm, which requires effort and practice to comprehend. Explanation of the effort required to comprehend recursion and the merge sort algorithm.', 'The pseudocode for the merge sort algorithm is introduced, which involves the algorithm calling itself and sorting the left and right halves before merging them together. Introduction of the merge sort algorithm pseudocode and its process of sorting and merging left and right halves.', 'The concept of merging two sorted halves of a list is demonstrated, emphasizing the process of comparing and weaving the elements together based on their sizes. Demonstration of the process of merging two sorted halves of a list by comparing and weaving elements based on their sizes.']}, {'end': 8135.597, 'start': 7642.889, 'title': 'Understanding merge sort algorithm', 'summary': 'Explains the merge sort algorithm, demonstrating the process of sorting and merging elements, highlighting the efficiency and trade-offs of merge sort in comparison to other sorting algorithms, such as selection sort and bubble sort, culminating in a visual comparison of the three algorithms.', 'duration': 492.708, 'highlights': ['Merge sort algorithm is explained, showcasing the process of sorting and merging elements, resulting in the sorted sublists. Demonstrates the step-by-step process of sorting and merging elements, leading to the creation of sorted sublists.', 'Efficiency and trade-offs of merge sort are emphasized, highlighting the advantage of using more memory for the merging process and its impact on the total running time, expressed as O(n log n). Emphasizes the trade-off of using more memory for the merging process and its impact on the total running time, expressed as O(n log n).', 'Comparison of merge sort with other sorting algorithms, such as selection sort and bubble sort, is presented visually, highlighting the design efficiency of merge sort. Presents a visual comparison of merge sort with other sorting algorithms, emphasizing the design efficiency of merge sort.']}], 'duration': 1088.185, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yb0PY3LX2x8/pics/yb0PY3LX2x87047412.jpg', 'highlights': ['The efficiency and trade-offs of merge sort are emphasized, highlighting the advantage of using more memory for the merging process and its impact on the total running time, expressed as O(n log n).', 'The concept of merging two sorted halves of a list is demonstrated, emphasizing the process of comparing and weaving the elements together based on their sizes.', 'The pseudocode for the merge sort algorithm is introduced, which involves the algorithm calling itself and sorting the left and right halves before merging them together.', 'Comparison of merge sort with other sorting algorithms, such as selection sort and bubble sort, is presented visually, highlighting the design efficiency of merge sort.', 'The base case in the draw function ensures that the function does not loop forever, preventing potential memory issues and bugs.']}], 'highlights': ['The chapter emphasizes the importance of search algorithms in programming.', "Efficiency and correctness are crucial in algorithm implementation, determining the program's performance and output.", 'The binary search algorithm demonstrated greater efficiency by finding the number in just three steps instead of seven, showcasing the advantage of dividing and conquering based on sorted numbers.', 'The chapter explores the decision-making process between linear search and sorting data, emphasizing the trade-offs involved and the different use cases where each approach may be more suitable.', 'Introducing a custom data type to tightly couple data elements and eliminate the vulnerabilities of using separate arrays', 'The efficiency of the selection sort algorithm was analyzed, resulting in the conclusion that it has a time complexity of O(n^2).', "Bubble sort's omega notation of n is an optimization for pre-sorted data.", 'The relevance of selection sort and bubble sort for small data sets is emphasized due to their relatively fast performance.', 'The efficiency and trade-offs of merge sort are emphasized, highlighting the advantage of using more memory for the merging process and its impact on the total running time, expressed as O(n log n).']}