Lecture 2 Concepts of Programming Languages

1. Lecture 2Concepts of Programming Languages Arne Kutzner Hanyang University / Seoul Korea

2. Topics • Reasons for Studying Concepts of Programming Languages • Programming Domains • Language Evaluation Criteria • Influences on Language Design • Language Categories • Language Design Trade-Offs • Implementation Characteristics of Languages • Significance of individual languages in 2019 Concepts of Programming Languages

3. Reasons for Studying Concepts of Programming Languages • Improved background for choosing appropriate languages • Reduction of the risk of wrong decisions • Better use of languages that are already known • Better understanding of significance of language implementations Concepts of Programming Languages

4. Programming Domains • Business applications • E.g. Middleware that implements some business process • Java, C++, C#, COBOL (still popular here!) • Web programming • Markup (HTML), Scripting (JavaScript (TypeScript), PHP etc.), general-purpose (e.g., Java), • General purpose applications like Photoshop, Autocad, Word etc. • Efficiency is important here • C++, C, Delphi • Systems programming / Operating System implementation • Low level, code efficiency is very important • C, Assembler • Scientific applications • E.g. Simulations; computational expensive tasks • Python, R, Fortran, (C, C++) • Artificial intelligence • C++, Python: Deep learning, TensorFlow, etc. • Older: Experimental work with languages like LISP (Scheme) and Prolog • Gaming, Embedded Systems, IoT … Concepts of Programming Languages

5. Language Evaluation Criteria • Readability: Is this code easily readable? • Writability: Do you like this coding?++++++++[>++++[>++>+++>+++>+<<<<-]>+>+>->>+[<]<-]>>.>---.+++++++..+++.>>.<-.<.+++.------.--------.>>+.>++. • Hello World in Brainfuck (http://esolangs.org/wiki/Brainfuck) • Reliability: unexpected crashes, blue screen of death • Cost: $, €, £ … Concepts of Programming Languages

6. Evaluation Criteria: Readability / Writability • Overall readability/writability • Are the constructs of the language self describing/intuitive/well human readable … • Syntax considerations • Special symbols and their meaning (e.g. creation of compound statements) • Special words, meaningful keywords • Data types and structures • Adequate predefined data types and structures • The presence of adequate facilities for defining new data structures Concepts of Programming Languages

7. Evaluation Criteria: Readability / Writability • Support for abstraction • The ability to define and use complex structures or operations in ways that allow details to be ignored • Expressivity • List comprehensions (Python, Haskell) etc. • Range-based for loops Concepts of Programming Languages

8. Evaluation Criteria: Reliability • Static type checking vs. dynamic type checking • Recognition of type errors during compile time / runtime • Exception handling • Intercept run-time errors and take corrective measures Concepts of Programming Languages

9. Evaluation Criteria: Cost • Training programmers to use the language • Language implementation system: Costs for compilers • Reliability: poor reliability leads to high costs • Maintenance costs • Deployment costs Concepts of Programming Languages

10. Further Evaluation Criteria … • Portability • The ease with which programs can be moved from one implementation to another • Generality • The applicability to a wide range of applications • Well-definedness • The completeness and precision of the language’s official definition Concepts of Programming Languages

11. Influences on Language Design • Computer Architecture • Architecture as driving factor of language design. • E.g. Von Neumann Architecture • OpenCL/CUDA for computing on GPUs • Programming Methodologies • Abstract data types • Concept of object orientation • Computational models / Mathematical models for computation • Lambda Calculus, Predicate Logic Concepts of Programming Languages

12. Von Neumann Architecture Concepts of Programming Languages

13. Programming Methodologies History / Mainstream developments • 1950s and early 1960s: Simple applications; worry about machine efficiency • Late 1960s: People efficiency became more important; readability, better control structures • structured programming • top-down design and step-wise refinement • Late 1970s: Process-oriented to data-oriented • data abstraction • Middle 1980s: Object-oriented programming • Data abstraction + Inheritance + Polymorphism • Appearance of C++, Eiffel … Concepts of Programming Languages

14. Imperative Languages • Characteristics: • Variables model memory cells • Assignment statements used for assigning values to memory cells • Iteration represents central concept • Inspired by von Neumann computers • Data and programs stored in memory • Memory is separate from CPU • Instructions and data are piped from memory to CPU Concepts of Programming Languages

15. Language Categories / Families • Imperative / Object Oriented • Comprises languages that support object-oriented programming • Comprises scripting languages • Examples: C++, C, Java, C#, Python, JavaScript (TypeScript) • Markup and related • No logic, only pure descriptive: HTML, CSS, XML • Hybrids: PHP (Visualization plus logic), XSLT (XML plus logic) • Functional • Motivated by Lambda Calculus • Examples: LISP, Scheme, Haskell • Logic • Rule-based (rules are specified in no particular order) • Example: Prolog Concepts of Programming Languages

16. Language Design Trade-Offs • Reliability vs. Cost of execution • Example: Java demands all references to array elements be checked for proper indexing, which leads to increased execution costs • Writability (flexibility) vs. Reliability • Example: C pointers are powerful and very flexible but they are unreliable Concepts of Programming Languages

17. Implementation Characteristics of languages • Compilation • Programs are translated directly into machine language • Pure Interpretation • Programs are interpreted by an execution context known as an interpreter • Hybrids (Bytecode-based) • A compromise between compilers and pure interpreters Concepts of Programming Languages

18. Compilation • Translate high-level program (source code) into machine code (executable file) • Phases of compilation process: • Lexical analysis: converts characters in the source program into lexical units • Syntax analysis: transforms lexical units into parse trees which represent the syntactic structure of program • Semantics analysis: generate intermediate code • Optimization: automatically apply improvements • Code generation: machine code is generated and written to "objects files" • Linking: collect "objects files" for creating an executable Concepts of Programming Languages

19. Interpretation • Advantages: • No compilation involved • Boost portability! • Disadvantages: • Errors are recognized during runtime • No static type-check, because of the absence of compilation • Slow execution speed, if no clever just-in-time compilation is involved. • Significant in the area of Web programming: JavaScript, PHP Concepts of Programming Languages

20. Bytecode-based Systems • A compromise between platform-specific compilation (e.g. C++) and pure interpretation • Program code is first translated to an intermediate code (called byte code) for later execution on a virtual machine • Much Faster than pure interpretation • Advantage: Portability • Examples • Java, C# Concepts of Programming Languages

21. Bytecode-based Systems -Programming Workflow Write Source Code program text in human readable form Source Code all 5 steps of compilation Compile Source Code represents anintermediate code Byte Code using a byte-code interpreter Execute Byte Code Concepts of Programming Languages

22. Just-in-Time Compilation • Optimization for byte-code interpretation • Instead of interpreting the byte-code the byte-code is first compiled into machine code and this machine code is executed directly on processor level • Higher performance compared to pure interpretation • JIT-compilation requires initially extra time. So, it delays code execution / program start. Concepts of Programming Languages

23. Preprocessors • A preprocessor processes/changes source code before it is compiled • Works like a macro mechanism and implements a text to text transformation • C, C++ preprocessor • expands #include, #define, and similar macros • Not popular outside C and C++ • Main disadvantage: Compiler error messages can become quite cryptic/strange Concepts of Programming Languages

24. Significance of individual languages in 2019 2019 Java Programming