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

Lecture 2

Concepts of Programming Languages

Arne Kutzner

Hanyang University / Seoul Korea

Concepts of Programming Languages L2.2

Topics

• Reasons for Studying Concepts of Programming Languages

• Programming Domains• Language Evaluation Criteria• Influences on Language Design• Language Categories• Language Design Trade-Offs• Implementation Methods• Programming Environments


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


Programming Domains• Business applications

– E.g. Middleware that implements some business process– Java, COBOL (still popular here!)

• Web programming– Languages: markup (e.g., HTML), scripting (e.g., PHP), general-purpose (e.g.,

Java)• General purpose applications

– Examples: Photoshop, Autocad, Word ….– Reliability and efficiency are important

• Systems programming / Operating System implementation– Low level, code efficiency is very important– C, Assembler

• Scientific applications– E.g. Simulations; computational expensive tasks– Fortran, (C, C++)

• Artificial intelligence– Experimental work with languages like LISP (Scheme) and Prolog– However, still on the level artificial stupidity


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: $ $ $ $ $ …


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


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– A set of relatively convenient ways of

specifying operations– Strength and number of operators and

predefined function


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


Evaluation Criteria: Cost

• Training programmers to use the language• Language implementation system: Availability

of free compilers• Reliability: poor reliability leads to high costs• Maintenance costs• Deployment costs


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


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


Von Neumann Architecture


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 …


Imperative Languages

• 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

• Characteristics of imperative languages– Variables model memory cells– Assignment statements used for assigning values to

memory cells– Iteration represents central concept– Popular examples: C, Pascal


Language Categories / Families

• Imperative– Comprises languages that support object-oriented programming– Comprises scripting languages– Examples: C, Java, Perl, JavaScript, Visual BASIC .NET, C++, C#

• Markup/programming hybrid – Markup languages extended to support some programming– Examples: HTML, XML, PHP, XSLT

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

given parameters– Examples: LISP, Scheme, Haskell

• Logic– Rule-based (rules are specified in no particular order)– Example: Prolog


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


Implementation Characteristics of languages

• Compilation– Programs are translated directly into machine

language

• Pure Interpretation– Programs are interpreted by another program

known as an interpreter

• Hybrid Implementations– A compromise between compilers and pure

interpreters


Compilation• Translate high-level program (source code) into

machine code (executable file)• Slow translation, fast execution• Phases of compilation process:

1. Lexical analysis: converts characters in the source program into lexical units

2. Syntax analysis: transforms lexical units into parse trees which represent the syntactic structure of program

3. Semantics analysis: generate intermediate code4. Optimization: automatically apply improvements5. Code generation: machine code is generated


Additional Compilation Terminology

• Linking: the process of collecting “objects files” for creating an executable file as output.


Pure Interpretation

• Advantages– No translation/compilation required

• Disadvantages– Errors are recognized during runtime– Slow execution speed (10 to 100 times slower

than compiled programs)– No static type-check, because of the absence of

compilation

• Significant in the area of Web scripting languages (e.g. JavaScript, PHP)


Hybrid Implementation Systems

• A compromise between compilers and pure interpreters

• A program code is first translated to an intermediate code (called byte code) for later execution on a virtual machine

• Faster than pure interpretation• More portable than compiled code• Examples

– Java, C#


Hybrid Implementations

Write Source Code

Source Code

Compile Source Code

Byte Code

Execute Byte Code

all 5 steps of compilation

using a byte-code interpreter

represents anintermediate code

program text in human readable form


Just-in-Time Compilation

• Optimization for hybrid implementations• Instead of interpreting the byte-code the byte-code is

first compiled into machine code and this machine code is executed direct on processor level

• Higher performance compared to interpretation• JIT-compilation requires initially extra time. So it

delays code execution / program start• Nowadays standard with most hybrid

implementations


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


Integrated Development Environments

• Not part of the programming language itself; only supportive tools for convenient software development

• Popular examples:– Microsoft Visual Studio tools:

• Supports MS-compiler for C#, Visual BASIC.NET, Jscript, J#, and C++

– Eclipse • Open programming environment that supports many

programming languages

– NetBeans• An integrated development environment for Java provided by

Oracle

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

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