Concepts of Programming Languages (CS320) Lecture Notes PDF

Concepts of Programming Languages (CS320) Dr. Osama Helmy Email: [email protected] Chapter 1 Topics Reasons for Studying Concepts of Programming Languages Programming Domains Programming Language Genealogy Language Evaluation Criteria Influences on La...

Concepts of Programming Languages (CS320) Dr. Osama Helmy Email: [email protected] Chapter 1 Topics Reasons for Studying Concepts of Programming Languages Programming Domains Programming Language Genealogy Language Evaluation Criteria Influences on Language Design Language Categories Language Design Trade-Offs Implementation Methods Programming Environments 1-2  Reasons for Studying Concepts of Programming Languages Increased ability to express ideas Improved background for choosing appropriate languages Increased ability to learn new languages Better understanding of significance of implementation Better use of languages that are already known Overall advancement of computing 1-3  Programming Domains Scientific applications – Large numbers of floating point computations; use of arrays – Fortran Business applications – Produce reports, use decimal numbers and characters – COBOL Artificial intelligence – Symbols rather than numbers manipulated; use of linked lists – LISP, Prolog and C Systems programming – Need efficiency because of continuous use – C Web Software – Eclectic collection of languages: markup (e.g., HTML), scripting (e.g., JavaScript and PHP), general-purpose (e.g., Java) 1-4 Programming Language Genealogy 1-5 Language Evaluation Criteria 1-6 Language Evaluation Criteria(2) 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 1-7 Evaluation Criteria: Readability Overall simplicity – A manageable set of features and constructs – Minimal feature multiplicity – Minimal operator overloading Orthogonality – A relatively small set of primitive constructs can be combined in a relatively small number of ways – Every possible combination is legal Data types – Adequate predefined data types Syntax considerations – Identifier forms: flexible composition – Special words and methods of forming compound statements – Form and meaning: self-descriptive constructs, meaningful keywords 1-8 Evaluation Criteria: Writability Simplicity and orthogonality – Few constructs, a small number of primitives, a small set of rules for combining them 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 functions 1-9 Evaluation Criteria: Reliability Type checking – Testing for type errors Exception handling – Intercept run-time errors and take corrective measures Aliasing – Presence of two or more distinct referencing methods for the same memory location Readability and writability – A language that does not support “natural” ways of expressing an algorithm will require the use of “unnatural” approaches, and hence reduced reliability 1-10 Evaluation Criteria: Cost Training programmers to use the language Writing programs (closeness to particular applications) Compiling programs Executing programs Language implementation system: availability of free compilers Reliability: poor reliability leads to high costs Maintaining programs 1-11 Evaluation Criteria: Others 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 1-12 Influences on Language Design Computer Architecture – Languages are developed around the prevalent computer architecture, known as the von Neumann architecture Program Design Methodologies – New software development methodologies (e.g., object-oriented software development) led to new programming paradigms and by extension, new programming languages 1-13 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 1-14 The von Neumann Architecture 1-15 The von Neumann Architecture Fetch-execute-cycle (on a von Neumann architecture computer) initialize the program counter repeat forever fetch the instruction pointed by the counter increment the counter decode the instruction execute the instruction end repeat 1-16 Programming Methodologies Influences 1950s and early 1960s: Simple applications; worry about machine efficiency Late 1960s: People efficiency became 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 1-17 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: C, Java, Perl, JavaScript, Visual BASIC.NET, C++ Functional – Main means of making computations is by applying functions to given parameters – Examples: LISP, Scheme, ML, F# Logic – Rule-based (rules are specified in no particular order) – Example: Prolog Markup/programming hybrid – Markup languages (HTML and XML) extended to support some programming – Examples: JSTL, XSLT 1-18 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 Readability vs. writability Example: APL provides many powerful operators (and a large number of new symbols), allowing complex computations to be written in a compact program but at the cost of poor readability Writability (flexibility) vs. reliability – Example: C++ pointers are powerful and very flexible but are unreliable 1-19 Implementation Methods Compilation – Programs are translated into machine language; includes JIT systems – Use: Large commercial applications Pure Interpretation – Programs are interpreted by another program known as an interpreter – Use: Small programs or when efficiency is not an issue Hybrid Implementation Systems – A compromise between compilers and pure interpreters – Use: Small and medium systems when efficiency is not the first concern 1-20 Layered View of Computer The operating system and language implementation are layered over machine interface of a computer 1-21 Compilation Translate high-level program (source language) into machine code (machine language) Slow translation, fast execution Compilation process has several phases: – 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 – code generation: machine code is generated 1-22 The Compilation Process 1-23 Additional Compilation Terminologies Load module (executable image): the user and system code together Linking and loading: the process of collecting system program units and linking them to a user program 1-24 Von Neumann Bottleneck Connection speed between a computer’s memory and its processor determines the speed of a computer Program instructions often can be executed much faster than the speed of the connection; the connection speed thus results in a bottleneck Known as the von Neumann bottleneck; it is the primary limiting factor in the speed of computers 1-25 Pure Interpretation No translation Easier implementation of programs (run-time errors can easily and immediately be displayed) Slower execution (10 to 100 times slower than compiled programs) Now rare for traditional high-level languages Significant comeback with some Web scripting languages (e.g., JavaScript, PHP) 1-26 Pure Interpretation Process 1-27 Hybrid Implementation Systems A compromise between compilers and pure interpreters A high-level language program is translated to an intermediate language that allows easy interpretation Faster than pure interpretation Examples – Perl programs are partially compiled to detect errors before interpretation – Initial implementations of Java were hybrid; the intermediate form, byte code, provides portability to any machine that has a byte code interpreter and a run-time system (together, these are called Java Virtual Machine) 1-28 Hybrid Implementation Process 1-29 Just-in-Time Implementation Systems Initially translate programs to an intermediate language Then compile the intermediate language of the subprograms into machine code when they are called Machine code version is kept for subsequent calls JIT systems are widely used for Java programs.NET languages are implemented with a JIT system In essence, JIT systems are delayed compilers 1-30 Preprocessors Preprocessor macros (instructions) are commonly used to specify that code from another file is to be included A preprocessor processes a program immediately before the program is compiled to expand embedded preprocessor macros A well-known example: C preprocessor – expands #include, #define, and similar macros 1-31 Programming Environments A collection of tools used in software development UNIX – An older operating system and tool collection – Nowadays often used through a GUI (e.g., CDE, KDE, or GNOME) that runs on top of UNIX Microsoft Visual Studio.NET – A large, complex visual environment Used to build Web applications and non-Web applications in any.NET language NetBeans – Related to Visual Studio.NET, except for applications in Java 1-32