Introduction to programming languages Algorithms flowcharts Slides borrowed

Introduction to programming languages, Algorithms & flowcharts Slides borrowed from Instructor: Wajih Alouini 1

What are Program and programming language? • Program : Set of instructions which a computer can “interpret” to solve problems, make calculations, perform tasks, etc. • Programming Language : A formal language that is intended for the expression of computer programs 2

Why study programming languages? • Programming languages are important for students in all disciplines of engineering because they are the primary tools of the central activity of any science. 3

Why study programming languages? (cont. ) • To improve your ability to develop effective algorithms and to improve your use of your existing programming language. • To increase your vocabulary of useful programming constructs. • To allow a better choice of programming languages. • To make it easier to learn a new language. 4

A short history of programming Languages 1950 : Numerically based languages. FORTRAN (55) – Business languages. COBOL(60) – Artificial intelligence languages. LISP, ALGOL(58) • LISP, FORTRAN (55) ALGOL • 1970 : PLs Ada, C, Pascal, Smalltalk • 1980 : Development of functional programming: ML, Miranda Object-oriented programming: Smalltalk, C++ 5

A short history of programming languages (cont. ) • 90 s: – – – Fourth-generation languages Productivity tools (such as spreadsheets) Visual languages : Delphi Scripting languages : Perl Expert systems shells Network computing : Java 6

Low-level vs. High-level Programming Languages • Low-level: – Machine code – Assembly • High-level: (abstraction from the computer details) – Basic, C, Java, Pascal, C++, Perl, Python, … 7

Styles of Computer Programming • Procedural: procedures, routines, subroutines, methods, or functions – e. g. C, Pascal, Basic, Fortran • Functional – Mathematical functions – e. g. Lisp, Erlang, Haskell, ML, … • Object-oriented – e. g. C++, Java, Smalltalk • Rule-based (or Logic) : facts, rules – e. g. Prolog 8

Examples (1/5) • Fibonacci numbers – Fn = Fn-1 + Fn-2 , n>=2 F 0 = 0, F 1 = 1 • How to program? • 0, 1, 1, 2, 3, 5, 8, 13 9

Examples (2/5) • Functional: (Haskell) – fib 0 = 0 fib 1 = 1 fib n = fib (n-1) + fib (n-2) 10

Examples (3/5) • Procedural: (C) – int fib(int n) { int first = 0, second = 1; for (int i=0, i<n; i++) { int sum = first+second; first = second; second = sum; } return first; } 11

Examples (4/5) • Assembly: (in x 86 using MASM syntax) – mov edx, [esp+8] cmp edx, 0 ja @f mov eax, 0 ret @@: cmp edx, 2 ja @f mov eax, 1 ret @@: push ebx mov ebx, 1 mov ecx, 1 @@: lea eax, [ebx+ecx] cmp edx, 3 jbe @f mov ebx, ecx mov ecx, eax dec edx jmp @b @@: pop ebx ret 12

Examples (5/5) • Machine code – 8 B 542408 83 FA 0077 06 B 80000 C 383 FA 027706 B 8010000 00 C 353 BB 01000000 B 9010000 008 D 0419 83 FA 0376 078 BD 98 B C 84 AEBF 1 5 BC 3 13

Attributes of a good language • Ease of program verification – Proof of correctness, desk checking, test – Simplicity of semantic and syntax • Programming environment • Portability of programs • Cost of use – – Program execution Program translation Program creation, testing, and use Program maintenance 14

Attributes of a good language (another view: to make a software reliable, maintainable, efficient) • Reliability – – – Writability Readability Simplicity Safety (no goto, no pointers) Robustness (undesired events can be trapped, like arithmetic overflow, invalid inputs) • Maintainability – Factoring (modularity) – Locality • Efficiency 15

Issues for all Languages • Can it be understood by people and processed by machines? – although translation may be required • Sufficient expressive power? – can we say what needs to be said, at an appropriate level of abstraction? 16

Translation • Compilation – Translate into instructions suitable for some other (lower level) machine – During execution, that machine maintains program state information • Interpretation – May involve some translation – Interpreter maintains program state 17

Trade-offs • Compilation – lower level machine may be faster, so programs run faster – compilation can be expensive – examples: C (and Java? ) • Interpretation – more ability to perform diagnostics (or changes) at run-time – examples: Basic, UNIX shells, Lisp 18