Programming Languages: Summary, Study notes of Programming Languages

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Programming Languages, Summary

CSC419; Odelia Schwartz

Programming Domains

• Scientific applications
  • Large numbers of floating point computations; use of arrays
  • Fortran (more recently though not stressed in book: Matlab, Python)
• Business applications
  • Produce reports, use decimal numbers and characters
  • COBOL
• Artificial intelligence
  • Symbols rather than numbers manipulated; use of linked lists
  • LISP

Language Categories

• Imperative
  • Central features are variables, assignment statements, and

iteration

• Include languages that support object-oriented programming
• Include scripting languages
• Include the visual languages
• Examples: Ada, C, Java, Perl, JavaScript, Ruby, Visual

BASIC .NET, C++, Python, …

• Functional
  • Main means of making computations is by applying functions to

given parameters

• In pure languages, no side effects
• Examples: LISP, Scheme, ML, Haskell

Language Evaluation Criteria

• Readability: the ease with which programs can be read

and understood

• Writability: the ease with which a language can be

used to create programs

• Reliability: conformance to specifications (i.e., performs

to its specifications)

• Cost: the ultimate total cost

Computer Architecture Influence

• Well-known computer architecture: Von Neumann

• Imperative languages, most dominant, because of von

Neumann computers

• Data and programs stored in memory
• Memory is separate from CPU
• Instructions and data are piped from memory to CPU
• Basis for imperative languages
  • Variables model memory cells
  • Assignment statements model piping
  • Iteration is efficient

• We discussed Von Neumann bottleneck

Describing Syntax and Semantics

• BNF and context-free grammars are equivalent meta-

languages

• Well-suited for describing the syntax of programming languages

• An attribute grammar is a descriptive formalism that

can describe both the syntax and the semantics of a

language

• Three primary methods of semantics description

• Operation, axiomatic, denotational

Example Grammar for small language

→ begin <stmt_list> end <stmt_list> → | ; <stmt_list> → = → a | b | c → + | - |

Example derivation

=> begin <stmt_list> end

=> begin ; <stmt_list> end

=> begin = ; <stmt_list> end

=> begin A = ; <stmt_list> end

=> begin A = + ; <stmt_list> end

=> begin A = B + ; <stmt_list> end

=> begin A = B + C ; <stmt_list> end

=> begin A = B + C ; end

=> begin A = B + C ; = end

=> begin A = B + C ; B = end

=> begin A = B + C ; B = end

=> begin A = B + C ; B = C end

Example derivation

=> begin <stmt_list> end

=> begin ; <stmt_list> end

=> begin = ; <stmt_list> end

=> begin A = ; <stmt_list> end

=> begin A = + ; <stmt_list> end

=> begin A = B + ; <stmt_list> end

=> begin A = B + C ; <stmt_list> end

=> begin A = B + C ; end

=> begin A = B + C ; = end

=> begin A = B + C ; B = end

=> begin A = B + C ; B = end

=> begin A = B + C ; B = C end

We derived leftmost; could have also done rightmost

Parse Tree

• A hierarchical representation of a derivation

<stmt_list> C a = + B

Ambiguity in Grammars

• A grammar is ambiguous if and only if it

generates a sentential form that has two or

more distinct parse trees

• Problematic for compilers since parse tree, and

therefore meaning of the structure, cannot be

determined uniquely

Static and Dynamic Binding

• A binding is static if it first occurs before run time and remains unchanged throughout program execution.
• A binding is dynamic if it first occurs during execution or can change during execution of the program

Categories of Variables by Lifetimes

• Static--bound to memory cells before execution begins and remains bound to the same memory cell throughout execution, e.g., C and C++ static variables