1. Why study programming languages?
Increased capacity to express ideas
Constructs we can express can be constrained by the language we know
Improved background for choosing appropriate language
Should choose language appropriate for task not just the one that we know
Increased ability to learn new languages
Learning new languages and learning language fundamentals enables us to learn other languages more easily
Better understanding of the significance of implementation
Aids in finding bugs
Enables us to write more efficient code
Better use of languages that are already known
looking at the concept of languages (threads, exceptions, polymorphism) encourages uses of those things in languages already known (Java)
Overall advancement of computing
Educated people will encourage use of good languages
Section 1.1

2. Computer Applications & Languages
Scientific
Number crunching, weather forecasting, codebreaking, plane/missile trajectories
Language requirements:
Real numbers
Large amount of calculations (hence efficient)
Arrays, matrices
Selection, Counting loops
Languages:
Assembly, Fortran, Algol and descendants of Algol (Pascal, Modula, Ada, PL/I)
Section 1.2

3. Computer Applications & Languages
Scientific Applications
Language requirements: reals, efficiency, arrays, loops
Languages: Fortran, assembly, Algol
Business
Financial transactions
Language requirements:
Report production
Exact (but low) precision (e.g., money)
Character data
Languages: COBOL, RPG
Section 1.2

4. Computer Applications & Languages
Scientific Applications: reals, efficiency, arrays, loops Fortran, assembly, Algol
Business Applications: reports, decimal precision, characters COBOL, RPG
Artificial Intelligence
Deductive systems, reasoning, machine learning
Language requirements:
Symbolic computation (“names” not numbers)
Lists of data (not arrays)
Recursion
Languages: LISP, Scheme, Prolog
Section 1.2

5. Computer Applications & Languages
Scientific Applications: reals, efficiency, arrays, loops Fortran, assembly, Algol
Business Applications: reports, decimal precision, characters COBOL, RPG
AI Applications: Symbolic computation, Lists of data, Recursion LISP, Scheme, Prolog
Systems Programming
Operating systems, compilers, debuggers, etc.
Language requirements:
FAST execution
External device interfaces
Languages: C, Assembly
Section 1.2

6. Computer Applications & Languages
Scientific Applications: reals, efficiency, arrays, loops Fortran, assembly, Algol
Business Applications: reports, decimal precision, characters COBOL, RPG
AI Applications: Symbolic computation, Lists of data, Recursion LISP, Scheme, Prolog
Systems Programming: fast, external devices C, Assembly
Web Software
Language requirements: dynamic web content, database access
Languages: XHTML, JavaScript, PHP, Ruby, Java
Section 1.2

7. Language Influences Architecture Programming Methodologies von Neumann
Memory
CPU
ALU
Programming Methodologies
Unstructured
Procedure-oriented (top-down, functions, …)
Data-oriented (ADT, OO)
Section 1.4

8. Language Categories (most important ones)
Imperative
Functional
Logic
Object oriented (extension of imperative)
Section 1.5

9. Imperative Programming Languages
Central features are variables and assignment statements
Design based on the von Neumann architecture
Variables model memory cells
Assignment statement models the “piping operation” – operands piped from memory to CPU; result piped from CPU to memory
Section 1.5

10. Functional Programming Languages
Main features are functions and function calls (recursion instead of iteration)
Design is based upon mathematical functions
Section 1.5

11. Logic programming languages
Also called rule-based languages and declarative languages
Programmer gives rules that specify what a solution looks like and not how desired solution is achieved
Section 1.5

12. Object Oriented Programming Languages
Provides a feature for building objects
Provides a method for specifying inheritance
Provides polymorphism
Same name for different functions (method overriding)
Dynamic binding of function call to function body
Section 1.5

13. Implementation methods
Compilation
Interpretation
Hybrid
Section 1.7

14. Compilation
Compiler translates program into machine language that is executed on the computer
Execution is fast
Section 1.7

15. Compilation source machine code Lexical analyzer Linker Syntax
executable
Semantic analyzer/
Intermediate code
generation
Optimizer
Code
generator
machine code
Section 1.7

16. Interpreter
Pure interpretation means there is no translation of the source program
Program called an interpreter is executed by the computer
Interpreter fetches/decodes/executes source program
Slower and requires more space than the compilation process
Section 1.7

17. Hybrid
Source program is translated into an intermediate code that is then interpreted
Examples
Java is translated into byte code that can be interpreted
Perl is compiled before execution in order to detect compilation errors (unlike shell languages)
Section 1.7