Editing 342: 1337: Part 2
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==Explanation== | ==Explanation== | ||
| − | This is the second part of five in the "[[:Category:1337|1337]]" series. The title 1337 is "L-eet," or "elite," using the {{w|Leet}} alphabet, a coding system used primarily on the internet (and on early text messaging | + | This is the second part of five in the "[[:Category:1337|1337]]" series. The title 1337 is "L-eet," or "elite," using the {{w|Leet}} alphabet, a coding system used primarily on the internet (and on early text messaging system), meant to provide a bit of {{w|obfuscation}} to plain text both to make it harder to read and to show off in a creative way using in-group jargon. |
| − | + | All comics in the series: | |
| − | * [[341: 1337: Part 1]] | + | *[[341: 1337: Part 1]] |
| − | * [[342: 1337: Part 2]] | + | *[[342: 1337: Part 2]] |
| − | * [[343: 1337: Part 3]] | + | *[[343: 1337: Part 3]] |
| − | * [[344: 1337: Part 4]] | + | *[[344: 1337: Part 4]] |
| − | * [[345: 1337: Part 5]] | + | *[[345: 1337: Part 5]] |
| + | This series was released on five consecutive days (Monday-Friday, probably because he wanted to release comic 404 on April fools' day) and not over the usual Monday/Wednesday/Friday schedule. | ||
"Like a ring in a bell" appears to be a reference to the {{w|Chuck Berry}} song {{w|Johnny B. Goode}}, in which Berry describes a young boy (like himself) who becomes a guitar-playing prodigy. The original lyric was "just like a-ringing a bell." Apparently, [[Help I'm trapped in a driver's license factory Elaine Roberts|Elaine Roberts]] learned to program as quickly, easily, and skillfully as Johnny (and Chuck) learned to play rock 'n' roll. | "Like a ring in a bell" appears to be a reference to the {{w|Chuck Berry}} song {{w|Johnny B. Goode}}, in which Berry describes a young boy (like himself) who becomes a guitar-playing prodigy. The original lyric was "just like a-ringing a bell." Apparently, [[Help I'm trapped in a driver's license factory Elaine Roberts|Elaine Roberts]] learned to program as quickly, easily, and skillfully as Johnny (and Chuck) learned to play rock 'n' roll. | ||
| − | + | {{w|Donald Knuth}} is a computer science Professor Emeritus at {{w|Stanford University}} who is famous for writing {{w|The Art of Computer Programming}} and developing the <span class="texhtml"><span style="font-family:cmr10, LMRoman10-Regular, Times, serif;">T<span style="text-transform:uppercase; vertical-align:-0.5ex; margin-left:-0.1667em; margin-right:-0.125em;">e</span>X</span></span> computerized typesetting system. He may not have a mountain hideaway (a reference to ''{{w|Kill Bill}}'', by the way as is the whole training sequence), but he would be one of the best mentors a budding hacker could have. | |
The {{w|A* search algorithm}} and {{w|Dijkstra's algorithm}} are {{w|Graph traversal|graph search}} {{w|algorithm}}s. And what study of algorithms would be complete without a healthy study about finding complexities? {{w|Computational complexity theory|Time complexity}} is the amount of time an algorithm takes to execute. Upper and lower bounds for complexity is written in {{w|Big O notation}}. Best possible execution of an algorithm is constant time, or O(1), said in words, for any given data set, no matter how large, the algorithm will always return the answer at the same time. However, constant time is extremely difficult to achieve; linear time (O(n)) is also very good. For more complex algorithms, [https://www.wolframalpha.com/input/?i=plot+x*log%28x%29 O( n*log(n) )] is good, but [https://www.wolframalpha.com/input/?i=plot+x*log%28log%28x%29%29 O( n*log(log(n)) )] is better. (Note that logarithms in different bases are proportional to each other. So, this would hold true for any base >1.) | The {{w|A* search algorithm}} and {{w|Dijkstra's algorithm}} are {{w|Graph traversal|graph search}} {{w|algorithm}}s. And what study of algorithms would be complete without a healthy study about finding complexities? {{w|Computational complexity theory|Time complexity}} is the amount of time an algorithm takes to execute. Upper and lower bounds for complexity is written in {{w|Big O notation}}. Best possible execution of an algorithm is constant time, or O(1), said in words, for any given data set, no matter how large, the algorithm will always return the answer at the same time. However, constant time is extremely difficult to achieve; linear time (O(n)) is also very good. For more complex algorithms, [https://www.wolframalpha.com/input/?i=plot+x*log%28x%29 O( n*log(n) )] is good, but [https://www.wolframalpha.com/input/?i=plot+x*log%28log%28x%29%29 O( n*log(log(n)) )] is better. (Note that logarithms in different bases are proportional to each other. So, this would hold true for any base >1.) | ||
| − | + | From the evidence that [[Mrs. Roberts]] has two children, a daughter named [[Help I'm trapped in a driver's license factory Elaine Roberts]], and a younger son named Bobby (presumably [[Robert'); DROP TABLE students;--]], nicknamed Little Bobby Tables), we can assume that she is the same mother from [[327: Exploits of a Mom]]. Of course, the title text here explains that Elaine is only her middle name (assuming canonicity of title-text). In the title text to [[327: Exploits of a Mom]], we learned that her first name is "Help I'm trapped in a driver's license factory". Mrs. Roberts appears to have had fun naming her children. | |
==Transcript== | ==Transcript== | ||
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:Cueball (narrating): When Elaine turned 11, her mother sent her to train under Donald Knuth in his mountain hideaway. | :Cueball (narrating): When Elaine turned 11, her mother sent her to train under Donald Knuth in his mountain hideaway. | ||
| − | :[Donald Knuth, drawn with hair only around his neck, is standing with a pointing stick at a chalk board with graph traversal patterns on it and two blocks of unreadable text the top may be a matrix. This small panel is also lower than the next panel, with | + | :[Donald Knuth, drawn with hair only around his neck, is standing with a pointing stick at a chalk board with graph traversal patterns on it and two blocks of unreadable text the top may be a matrix. This small panel is also lower than the next panel, with Cueballs narration above:] |
:Cueball (narrating): For four years she studied algorithms. | :Cueball (narrating): For four years she studied algorithms. | ||
:Donald Knuth: Child— | :Donald Knuth: Child— | ||
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:Elaine: Dijkstra's algorithm! | :Elaine: Dijkstra's algorithm! | ||
| − | :[Donald Knuth and Elaine are outside, seen from behind while they are both writing on a chalkboard with a thick line down the middle to separate their work. On both sides their writing can be seen but it is unreadable. Where there is only text visible on Donald Knuth's side there is also what appears to be a drawing or matrix at the top of Elaine's. But a similar thing could be behind Donald Knuth's head. Elaine is no longer wearing her hair in a ponytail but have long straight white hair like her mom | + | :[Donald Knuth and Elaine are outside, seen from behind while they are both writing on a chalkboard with a thick line down the middle to separate their work. On both sides their writing can be seen but it is unreadable. Where there is only text visible on Donald Knuth's side there is also what appears to be a drawing or matrix at the top of Elaine's. But a similar thing could be behind Donald Knuth's head. Elaine is no longer wearing her hair in a ponytail but have long straight white hair like her mom Mrs. Roberts. To the left there is a stump from a tree, some grass and maybe a puddle of water. Further back there is a small jagged hill and a flat horizon. To the right there are four mountain peaks and a flat high plateau towards the horizon. The frame of the panel does not include the top and bottom corner, but cuts a rectangular section of both places. In these two sections outside the panel is the last two paragraphs of Cueball's narrating:] |
:Cueball (narrating): Until one day she bested her master | :Cueball (narrating): Until one day she bested her master | ||
:Donald Knuth: So our lower bound here is O(n log n) | :Donald Knuth: So our lower bound here is O(n log n) | ||
