강의 내용 및 방법 접근방법 시험 수업은 75분(14:30-15:45), 혹시 부족하면 보강 Lambda Calculus, Proof of Correctness는 간단히 설명 리포트 2주일에 프로그램 1개 정도, term project는 없음 (ABEEK의 이론 과목임), 5월 말 이후 프로그램 숙제 없음 각 장의 문제풀기 및 다른 문제 제공 시험 중간, 기말 및 1~2회 정도의 쪽지시험 수업은 75분(14:30-15:45), 혹시 부족하면 보강

참고자료 Http://borame.cs.pusan.ac.kr/lecture 강의참고자료 (한글) 2002년 강의 내용 2002년 리포트, 기타 참고사항 2003, 2004, 2005, 2006, 2007년 강의노트 다른 대학교, 자료, 우균 교수 자료(한글) 참고 강의 중에 이해가 안 되는 부분은 언제나 홈페이지의 묻고 답하기에 질문할 수 있음

Introduction Programming Language Design and Implementation (4th Edition) by T. Pratt and M. Zelkowitz Prentice Hall, 2001 Sections 1-1.3.2

언어란? 생각을 표현하는 도구!! 정보를 교환하는 도구!! 개념화 : 물체(Object), 물체와 관계, 추상화 중력의 법칙, 예측 인간은 전체를 듣지 않고도 부분을 이해함, 스스로 보완하여 인식함 프로그래밍언어 !! 우리의 생각을 컴퓨터가 처리할 수 있게 표현하는 도구 조금만 틀려도 이해 못함 오류가 없는 프로그램은 만들 수 없으며, 인간이 1,000만 줄 이상 프로그램은 만들 수 없다. (조던 폴락) 기계와 인간 간의 간격을 줄일수록 바람직함(추상화 단계가 높아져야 함) 기계뿐 아니라 인간도 이해해야 함 (쉽게 프로그램할 수 있어야)

Organization of Programming Languages Understand how languages are designed and implemented 구조 Lexicon – What sorts of words are legal? Syntax -- What a program looks like? Semantics -- What a program means? Implementation -- How a program executes Understand most appropriate language for solving specific problems, For example: Pascal, C, Perl -- procedural, statement oriented C++, Java, Smalltalk -- Object oriented ML, Lisp -- Functional Prolog -- Rule-based JavaScript, PHP, ASP.net – Procedural, Event-driven accessing

Language Goals During 1950s--1960s - Compile programs to execute efficiently. There is a direct connection between language features and hardware - integers, reals, goto statements Programmers cheap; Machines expensive; Keep the machine busy But today Compile programs that are built efficiently CPU power and memory very cheap Direct connection between language features and design concepts - encapsulation, records, inheritance, functionality, assertions Event-driven programming, Service-oriented approach, Web-service, Very High-level Language

Python Python is a general-purpose, high-level programming language. Its design philosophy emphasizes programmer productivity and code readability. Python's core syntax and semantics are minimalist, while the standard library is large and comprehensive. Python supports multiple programming paradigms (primarily functional, object oriented and imperative), and features a fully dynamic type system and automatic memory management; it is thus similar to Perl, Ruby, Scheme, and Tcl. Python was first released by Guido van Rossum in 1991.[3] The language has an open, community-based development model managed by the non-profit Python Software Foundation. While various parts of the language have formal specifications and standards, the language as a whole is not formally specified. The de facto standard for the language is the CPython implementation.

Why study programming languages? (1) To improve your ability to develop effective algorithms Improper use of recursion Object-oriented programming, logic programming, concurrent programming To improve your use of your existing programming language Data structures for arrays, strings, lists, records, set, bag, table (associative array) Malloc()  garbage collection Implementation details of recursion, object classes, subroutine calls, exception(event) handling … Service-oriented developing Web-service, Semantic web, Script language

Why study programming languages? (2) To increase your vocabulary of useful programming constructs Increase programming vocabulary and its implementation tech. Coroutine, Semaphore, event-driven programming, associative array Named parameter (Ada, Python, Smalltalk, Common Lisp) Name mangling (name decoration) To allow a better choice of programming language Numeric computation : C, FORTRAN, Ada AI : LISP, Prolog Internet applications : Perl, Java, HTML, XML, Web Service(SOAP), PHP, ASP.net, Python

Why study programming languages? (3) To make it easier to learn a new language Web programming (JavaScript, PHP), Semantic web Python To make it easier to design a new language User interface design *** C, COBOL, SMALLTALK의 덧셈의 속도차이를 초래하는 언어개념 및 구현의 차이

Evolution of software architecture 1950s - Large expensive mainframe computers ran single programs (Batch processing) 1960s - Interactive programming (time-sharing) on mainframes 1970s - Development of Minicomputers and first microcomputers. Apple II. Early work on windows, icons, and PCs at XEROX PARC 1980s - Personal computer - Microprocessor, IBM PC and Apple Macintosh. Use of windows, icons and mouse 1990s - Client-server computing - Networking, The Internet, the World Wide Web 2000s - P2P, Grid Computing, Web Service, Event-driven approach, Service-oriented programming, Script language, …

Attributes of a good language (1) Clarity, simplicity, and unity - provides both a framework for thinking about algorithms and a means of expressing those algorithms Conceptual integrity 나쁜 예: APL, SNOBOL4 Orthogonality - every combination of features is meaningful Fewer exceptions  C언어에서 !!! Logical errors and inefficiency

Attributes of a good language(2) Naturalness for the application - program structure reflects the logical structure of algorithm Sequential algorithm, concurrent algorithm, logic algorithm, non-deterministic algorithm Appropriate data structures, operations, control structures, natural syntax Support for abstraction - program data reflects problem being solved Data abstraction <D,O,C> Encapsulation

Attributes of a good language (3) Ease of program verification - verifying that program correctly performs its required function Verification/validation standard, or specification requirements the needs of the intended end-user or customer Comments, assert() Design specification Programming environment - external support for the language Debugger, syntax-directed editor Supporting function, platforms Smalltalk Supporting all the software lifecycle phases

Attributes of a good language (continued) Portability of programs - transportability of the resulting programs from the computer on which they are developed to other computer systems Transportability C, C++, Pascal  Java (Byte-code) ML : single source implementation Cost of use - program execution, program translation, program creation, and program maintenance Code optimization, (Smalltalk, Perl), lifecycle costs

Language paradigms Imperative languages Goal is to understand a machine state (set of memory locations, each containing a value) Statement oriented languages that change machine state (C, Pascal, FORTRAN, COBOL) Syntax: S1, S2, S3, ... Applicative (functional) languages Goal is to understand the function that produces the answer Function composition is major operation (ML, LISP) Syntax: P1(P2(P3(X))) Programming consists of building the function that computes the answer

Language paradigms (continued) Rule-based languages Specify rule that specifies problem solution (Prolog, BNF Parsing) Other examples: Decision procedures, Grammar rules (BNF) Syntax: Answer  specification rule Programming consists of specifying the attributes of the answer Object-oriented languages Imperative languages that merge applicative design with imperative statements (Java, C++, Smalltalk) Syntax: Set of objects (classes) containing data (imperative concepts) and methods (applicative concepts)

New Paradigm Internet, Home Computing, Ubiquitous Computing, Embedded Computing, etc Languages and Compilers that are smart, small and safe Moveable code  agents Independent from machines and programming environments Supporting pragmatics or intelligence Java, XML, Mobile computing. Mobile code Event driven approach, Service-oriented Architecture, Web Service Supports multiple paradigm : Python

다음을 조사하라!! (1) 왜 ActiveX가 새로운 Windows(비스타)에서 문제를 발생하는가? 왜 우리나라에서 유달리 ActiveX를 많이 쓰는가? ActiveX 대신 문제를 해결하는 방법은? Wikipedia를 참고하라!!! (2) Orthogonality가 C언어에서 발생시킬 수 있는 오류의 예를 들어라! (3)우리가 사용하는 언어는 왜 프로그래밍 언어로 부적합한가?