Lecture 1: Introduction

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1 Programming Languages Lecture 1: Introduction Benjamin J. Keller Department of Computer Science, Virginia Tech

2 Programming Languages Lecture 1 Introduction 2 Lecture Outline Preview History of Programming Languages Course topics

3 Programming Languages Lecture 1 Introduction 3 Programming Languages Representation that allows humans to communicate with a computer Abstraction of a machine language Different languages provide different abstractions

4 Programming Languages Lecture 1 Introduction 4 Kinds of Abstractions Data abstractions primitive data types: numeric, characters, booleans, pointers structured types: arrays, records unit: support for ADTs, modules, packages, classes Control abstractions basic: assignment, goto, sequencing structured: conditionals, loops, procedures and functions unit: separately compiled units, modules, packages, concurrent tasks

5 Programming Languages Lecture 1 Introduction 5 Defining Languages Program sequence of symbols that specify a computation Programming Language a set of rules that specify which sequences of symbols constitute a program, and what computation the program describes. Syntax how program is formed Semantics what program does Pragmatics how language is used

6 Programming Languages Lecture 1 Introduction 6 Language Goals Languages designed for different purposes Fortran numerical computation Pascal teaching programming C low-level system programming Evaluate language with respect to goals of its design

7 Programming Languages Lecture 1 Introduction 7 Languages and Software Development Language design goals may conflict with large-scale system development Modern languages support specific design methodology/philosophy functional design object-based design encapsulation information-hiding Language influences how people think about programming

8 Programming Languages Lecture 1 Introduction 8 Language Paradigms Computer architecture led to imperative Others developed as different ways to solve problems Functional computation as expression evaluation, popular in AI and theoretical programming language communities. Logical computation as proving queries. AI and database query languages. Object-Oriented computation as manipulation of/or interaction of objects.

9 Programming Languages Lecture 1 Introduction 9 Language Requirements Universal if a problem can be solved on a computer, then can solve it in the language Natural (expressive) easy to express solutions Implementable Efficient writing, compilation, or execution Reliable ability to deal with exceptional behavior Maintainable easy to make changes to programs

10 Programming Languages Lecture 1 Introduction 10 History Trend from machine language toward high-level languages Trend from single programmer to teams of programmers Early Languages FORTRAN John Backus, IBM, Goals: efficient compilation of solutions to numerical problems. Multiple revisions (latest in 90 s). Algol 60 committee, Goals: numeric, block structure, recursion. Influential on most modern languages. COBOL committee, Goals: business data processing. Multiple revisions.

11 Programming Languages Lecture 1 Introduction 11 More Early History LISP John McCarthy, MIT, Functional core. Goals: List processing, symbolic manipulation (AI applications). APL Iverson, Harvard, Calculator language for array computations. SNOBOL 4 Griswold, Bell Labs, Goals: string processing with pattern matching. PL/I committee at IBM, Attempt to combine FORTRAN, COBOL, Algol 60. Large language difficult to learn and use.

12 Programming Languages Lecture 1 Introduction 12 More History Algol 68 Algol with orthogonal elements. Elegant, but hard to understand. Simula 67 simulation language based on Algol 60. Basis for most object-oriented languages. Pascal Wirth, ETH-Zurich, Teaching language designed to support structured programming. Simple and elegant.

13 Programming Languages Lecture 1 Introduction 13 Further Developments Module support for abstract data types: Clu, Mesa, Modula-2, Ada Object-oriented: Smalltalk (70 s), Eiffel, C++, Object Pascal, Java Functional: Scheme (80 s), ML (70 s), Miranda, Haskell Logical: Prolog, newer constraint languages

14 Programming Languages Lecture 1 Introduction 14 Fourth Generation Languages Languages in business applications Specialized packages of powerful commands with simplified syntax.

15 Programming Languages Lecture 1 Introduction 15 Family Tree of Important Languages 1960 APL Algol 60 Fortran PL/I COBOL Lisp Snobol Algol 68 Smalltalk Simula Pascal Clu C Prolog 1980 Eiffel Modula 2 Oberon Ada C++ ML Miranda Haskell ICON 1990 Ada 95 Java

16 Programming Languages Lecture 1 Introduction 16 Course Topics Language features: modules, classes, exception handling, generic types, etc. Functional, object-oriented, logical and imperative paradigms. Support for reliable programming: abstraction, encapsulation, information hiding, polymorphism, higher-order operators. Support for concurrency. Formal definition of programming languages. Compilers and interpreters. Run-time behavior of programming languages

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