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Programming Languages Structure

Programming Languages Structure. Introduction. Text/References. Robert W. Sebesta, “ Concepts of Programming Languages ”, Fourth Edition Addison-Wesley (1999). T.W. Pratt and M.V. Zelkowitz, “ Programming Languages – Design and Implementation ” Fourth Edition, Prentice-Hall (2001).

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Programming Languages Structure

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  1. Programming Languages Structure • Introduction

  2. Text/References • Robert W. Sebesta, “Concepts of Programming Languages”, Fourth Edition Addison-Wesley (1999). • T.W. Pratt and M.V. Zelkowitz, “Programming Languages – Design and Implementation” Fourth Edition, Prentice-Hall (2001). • Ravi Sethi, “Programming Languages - Concepts and Constructs” Second Edition, Addison-Wesley (1996).

  3. Course Assessment • Mid-term Exam 30% • Project 30% • Final exam 40%

  4. Why study Programming Language Concepts? • Increased capacity to express ideas • Improved background for choosing appropriate languages • Increased ability to learn new languages • Better understanding of the implementation of concepts • Increased ability to design new languages

  5. Program - Definitions • A program is a description of a set of actions that we want a computer to carry out. • A program is a model of some process in the real or mathematical world. • A program is a sequence of instructions for a machine to perform a specific task. • A notational system for describing computation in machine-readable and human-readable form

  6. Programming Domains • Scientific: Heavily based on numerical algorithms (Fortran, C) • Business Applications: Storage, retrieval, and formatting of data, reporting. (COBOL) • Artificial Intelligence: Symbolic computing, List directed processing (LISP, Prolog) • Systems Programming: Fast, Low level features (C) • Internet: Web based programming (Perl, Java) • Simulation: Process modeling (MATLAB, GPSS)

  7. Programming Paradigms: 1. Imperative • Statement oriented languages • Every statement changes the machine state • Computation is expressed by a sequence of actions. • Heavily based on von Neumann architecture • Provides variables, assignments, and iterative repetitions. • Examples: Fortran, C

  8. Programming Paradigms: 2. Declarative • Problem specification using relations or functions. • Functional programming (applying functions to given parameters). • Logic programming (deductive reasoning, rule based) • Examples: LISP, ML, Haskell, Prolog

  9. Programming Paradigms: 3. Concurrent • Parallel execution of processes. • Multi-tasking or multi-threading primitives. • Inter process communication and synchronization. • Helps in speeding up the execution of parallel algorithms • Examples: Concurrent C, Java, Fortran-90

  10. Programming Paradigms: 4. Object Oriented • Based on the concept of data abstraction. • Uses encapsulation (data hiding) • Supports inheritance (software reuse) • Suitable for programming in the large. • Examples: C++, Java, Smalltalk, Eiffel

  11. Programming Paradigms: 5. Scripting • Contains a set of commands (scripts) to be executed. • Works in conjunction with a larger application, or are interpreted. • Examples: Perl, Javascript.

  12. Language Evaluation Criteria • Readability • Writability • Reliability • Cost

  13. Readability • Simplicity (Small number of basic components, less amount of feature multiplicity, restricted operator overloading). • Limited Orthogonality (Ways by which primitive constructs can be combined). • Control Structures (Structured programming) • Data types and structures (Arrays, records..) • Syntax design (Closeness to intended purpose)

  14. Writability • Simplicity/Orthogonality • Support for abstraction (process abstraction and data abstraction) • Expressivity (convenient ways of specifying computation)

  15. Reliability • Type checking (Compile-time checking of types of variables) • Exception handling (Ability to intercept errors, take corrective measures and continue). • Restricted aliasing (Multiple names associated with the same memory cell).

  16. Cost • Cost of training • Cost of compiling (Compilation time) • Cost of execution (Optimization) • Cost of language implementation (Compiler, hardware etc). • Cost of maintenance (Repairs, changes and extensions)

  17. Implementation Methods 1. Compilation Source Program Machine Language Fetch-Execute Machine • Source programs are translated to machine language

  18. Implementation Methods 1. Compilation Source Program Lexical Analyzer Lexical units Syntax Analyzer Parse trees Intermediate Code Generator Symbol Table Optimization Intermediate code Code Generator Machine code

  19. Implementation Methods 2. Pure Interpretation Source Program Fetch-Execute Interpreter Virtual Machine Machine • Source programs are directly interpreted by another program • without any translation.

  20. Implementation Methods 3. Hybrid Implementation • Compilation followed by interpretation. • Perl (Compiled to detect errors before interpretation) • Java (Compiled to platform independent byte codes, and interpreted by the JVM)

  21. Programming Environments • Collection of tools used in the development of software. • Consists of a file system, a text editor, a linker, a compiler, a debugger, and development tools. • Helps increase productivity and quality. • Examples: Borland C++, Visual C++, Visual J++

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