What is Computer Science What is it that

What is Computer Science? What is it that distinguishes it from the separate subjects with which it is related? What is the linking thread which gathers these disparate branches into a single discipline? My answer to these questions is simple --- it is the art of programming a computer. It is the art of designing efficient and elegant methods of getting a computer to solve problems, theoretical or practical, small or large, simple or complex. C. A. R. (Tony)Hoare CPS 100 1. 1

Why is programming fun? What delights may its practitioner expect as a reward? First is the sheer joy of making things Second is the pleasure of making things that are useful Third is the fascination of fashioning complex puzzle-like objects of interlocking moving parts Fourth is the joy of always learning Finally, there is the delight of working in such a tractable medium. The programmer, like the poet, works only slightly removed from pure thought-stuff. Fred Brooks CPS 100 1. 2

Efficient Programming l Designing and building efficient programs efficiently requires knowledge and practice Ø Hopefully the programming language helps, it’s not intended to get in the way Ø Object-oriented concepts, and more general programming concepts help in developing programs Ø Knowledge of data structures and algorithms helps l Tools of the engineer/scientist/programmer/designer Ø A library or toolkit is essential, STL or wheel re-invention? Ø Programming: art, science, engineering? None or All? Ø Mathematics is a tool Ø Design Patterns are a tool CPS 100 1. 3

Course Overview l Lectures, Recitations, Quizzes, Programs Ø Recitation based on questions given out in previous week • Discuss answers, answer new questions, small quiz • More opportunities for questions to be answered. Ø Lectures based on readings, questions, programs • Online quizzes used to motivate/ensure reading • In-class questions used to ensure understanding Ø Programs • Theory and practice of data structures and OO programming • Fun, practical, tiring, … • Weekly programs and longer programs l Exams/Tests Ø Semester: closed book Ø Final: open book CPS 100 1. 4

Questions l If you gotta ask, you’ll never know Ø Louis Armstrong: “What’s Jazz? ” l If you gotta ask, you ain’t got it Ø Fats Waller: “What’s rhythm? ” l What questions did you ask today? Ø Arno Penzias CPS 100 1. 5

Tradeoffs l This course is about all kinds of tradeoffs: programming, structural, algorithmic Ø Programming: simple, elegant, quick to run/to program • Tension between simplicity and elegance? Ø Structural: how to structure data for efficiency • What issues in efficiency? Time, space, programmer-time Ø l Algorithmic: similar to structural issues How do we decide which choice to make, what tradeoffs are important? CPS 100 1. 6

See readwords. cpp l This reads words, how can we count different/unique words? tvector<string> list; string filename, word; cin >> filename; ifstream input(filename. c_str()); CTimer timer; timer. Start(); while (input >> word) { list. push_back(word); } timer. Stop(); cout << "read " << list. size() << " words in "; cout << timer. Elapsed. Time() << " seconds" << endl; CPS 100 1. 7

Tracking different/unique words l We want to know how many times ‘the’ occurs Ø Do search engines do this? Does the number of occurrences of “basketball” on a page raise the priority of a webpage in some search engines? • Downside of this approach for search engines? l Constraints on solving this problem Ø We must read every word in the file (or web page) Ø We must search to see if the word has been read before Ø We must process the word (bump a count, store the word) Ø CPS 100 Are there fundamental limits on any of these operations? Where should we look for data structure and algorithmic improvements? 1. 8

Search: measuring performance l How fast is fast enough? bool search(const tvector<string> & a, const string & key) // pre: a contains a. size() entries // post: return true if and only if key found in a { int k; int len = a. size(); for(k=0; k < len; k++) if (a[k] == key) return true; return false; } l l C++ details: parameters? Return values? Vectors? How do we measure performance of code? Of algorithm? Ø Does processor make a difference? PIII, G 4, ? ? ? CPS 100 1. 9

Tradeoffs in reading and counting l Read words, then sort, determine # unique words? Ø frog, rat, tiger, tiger l If we look up words as we're reading them and bump a counter if we find the word, is this slower than previous idea? Ø How do we look up word, how do we add word l Are there kinds of data that make one approach preferable? Ø What is best case, worst case, average case? l What's one function spec & implememtation to count # unique words in a list/vector of words Ø See readwords 3. cpp CPS 100 1. 10

Who is Alan Perlis? l l l It is easier to write an incorrect program than to understand a correct one Simplicity does not precede complexity, but follows it If you have a procedure with ten parameters you probably missed some If a listener nods his head when you're explaining your program, wake him up Programming is an unnatural act Won first Turing award http: //www. cs. yale. edu/homes/perlis-alan/quotes. html CPS 100 1. 11

Review/Preview: Anagrams/Jumbles l l Brute-force approach to finding anagrams/solving Jumbles Ø Brute-force often thought of as “lack of thought” Ø What if the better way requires too much thought? Ø What if there’s nothing better? nelir, nelri, neilr, neirl, nerli, neril, nleir, nleri, nlier, nlire, nlrei, nlrie, nielr, nierl, niler, nilre, nirel, … lenir, lenri, leinr, leirn, lerni, lerin, liner Ø What’s the problem here? Ø Is there a better method? CPS 100 1. 12

Brute force? permana. cpp // find anagram of word in word. Source // list is a vector [0, 1, 2, …, n] Permuter p(list); int count = 0; string copy(word); // makes copy the right length for(p. Init(); p. Has. More(); p. Next()) { p. Current(list); for(k=0; k < list. size(); k++) { copy[k] = word[list[k]]; } if (word. Source. contains(copy)) { cout << "anagram of " << copy << endl; break; // find first anagram only } } CPS 100 1. 13

Quantifying brute force for anagrams l On one machine make/test a word takes 10 -5 seconds/word Ø 9! is 362, 880: how long does this take? Ø What about a ten-letter word? l We’re willing to do some pre-processing to make the time to find anagrams quicker Ø Often find that some initialization/up-front time or cost saves in the long run Ø We need a better method than trying all possible permutations Ø What properties do words share that are anagrams? CPS 100 1. 14

Toward a faster anagram finder l Words that are anagrams have the same letters; use a letter fingerprint or signature/histogram to help find anagrams Ø Count how many times each letter occurs: “teacher” 1 0 2 0 0 1 0 0 0 “cheater” 1 0 2 0 0 1 0 0 0 0 0 l Store words, but use fingerprint for comparison when searching for an anagram Ø How to compare fingerprints using operator == Ø How to compare fingerprints using operator < l How do we make client programmers unaware of fingerprints? Should we do this? CPS 100 1. 15

Another anagram method l Instead of fingerprint/histogram idea, use sorted form of word Ø “gable” and “bagel” both yield “abegl” Ø Anagrams share same sorted form l Similarities/differences to histogram/fingerprint idea? Ø Both use canonical or normal/normalized form Ø Normalized form used for comparison, not for printing Ø When should this normal form be created? l When is one method preferred over the other? Ø Big words, little words? Different alphabets? DNA vs English? CPS 100 1. 16

OO and C++ features we’ll use l We’ll use an adapter or wrapper class called Anaword instead of a string Ø Clients can treat Anaword objects like strings, but the objects are better suited for finding anagrams than strings Ø The Anaword for “bear” prints as “bear” but compares to other Anaword objects as 1100100000010000 l C++ allows us to overload operators to help, not necessary but good cosmetically Ø Relational operators == and < • What about other operators: >, <=, >=, and != Ø l Stream operator << How should we implement overloaded operators? CPS 100 1. 17

Overloaded operators l In C++ we can define what operator == and operator < mean for an object (and many other operators as well) Ø This is syntactically convenient when writing code Ø C++ details can be cumbersome (see Tapestry Howto E) l In anaword. h there are four overloaded operators Ø Ø Ø l What about > and >= ; what about != ; others? What about printing, can we overload operator << ? How do we access private data for printing? Comparing? Overloaded operators are not necessary, syntactic sugar. CPS 100 1. 18

Overloaded operators (continued) l Typically operators need access to internal state of an object Ø Relational operators for Date, string, Big. Int? Ø Where is “internal state”? l For technical reasons sometimes operators should not be member functions: Big. Int b = enter. Big. Value(); if (b < 2) … if (2 > b) … Ø l We’d like to use both if statements, only the first can be implemented using Big. Int: : operator < (why? ) Use helper member functions: equals, less, to. String Ø Implement overloaded operators using helpers CPS 100 1. 19

Anaword objects with options l Can we use different canonical forms in different contexts? Ø Could have Anaword, Finger. Print. Anaword, Sort. Anaword Ø What possible issues arise? What behavior is different in subclasses? • If there’s no difference in behavior, don’t have subclasses l Alternative, make canonical/normalize method a class Ø Turn a function/idea into a class, then let the class vary to encapsulate different methods Ø Normalization done at construction time or later Ø Where is normalizer object created? When? CPS 100 1. 20