Lecture 1. Programming II. Iztok Savnik, FAMNIT. February, 2019.

Transcription

1 Lecture 1 Programming II Iztok Savnik, FAMNIT February,

2 Contents Course organization History of programmiing languages Concepts of programming languages Meta-Language ML Some benchmarks Method and aims of course What is happening in PL area?

3 Course organization Lectures Iztok Savnik Exercises Matjaž Krnc, László Hajdu Homeworks Writting programs in Ocaml 3 homeworks

4 Grading Written exam 40% Oral exam 30% Homeworks 30% Each part must be positive! 4

5 Literature 1. John Mitchell, Concepts in Programming Languages, Cambridge Univ Press, Iztok Savnik, Jan Karabas, Concepts of programming languages, Lecture notes (in English), FAMNIT, Michael L. Scott, Programming Language Pragmatics (3rd ed.) Elsevier,

6 Overview of PL Assembler Fortran IPL, Cobol Imperative languages Algol Prog.language C Pascal, Modula Functional languages Lisp ML Haskell Object languages C++, Objective C Java, Eifel Ruby High-level languages Electronics Information systems Integration languages Script languages System languages Web languages User interfaces Python, Perl, PhP, JSP, ASP Prolog Sicstus Prolog SWI-Prolog Datalog Lambda Prolog

7

8 Charles Babbage The origins of the digital programmable computer English mathematician, philosopher, inventor and mechanical engineer. In 1837 he has designed Analytical engine, the first mechanical computer, that led to the design of more complex electronic computers. The anlytical engine mechanical computation of arithmetic operations branching loops where the results of the previous computation are taken as an input to the following iterations. Turing-complete machine

9 Electronic computers The first electromechanical computer German civil engineer and inventor Konrad Zuse Z1, Z2, Z3, 1936 and 1945, totally independent Loops but no branching, shown to be Turing-complete General-purpose electronic computer University of Pennsylvania ENIAC (Electronic Numerical Integrator and Computer) 10 digit arithmetic, branching, loops, procedures

10 Electronic computers Mark 1, Mark 2, Mark 3 ASCC (Automatic Sequence Controlled Calculator) Developed by Harvard University in 1944 Original concept presented to IBM by H.Aiken in 1937 Following Charles Babbage, loops but no branching von Neumann architecture Princeton arhitecture, 1945 First Draft of a Report on the EDVAC Principal abstraction, representation of the basic function of computers central processing unit, main memory and input/output devices

11 Plankalkuel The first programming language Konrad Zuse German civil engineer and inventor Floating-point mechanical digital calculator Z1 Improved versions Z2 and Z3 in 1941 Telephone relays for memory Presented to the public Concepts Sequence of arithmetical operations Loops included No branching operation

12 First compiler A-O programming language Algorithmic Language version 0 UNIVAC I computer Grace Hopper in 1951, 1952 Program in A-0 language was a sequence of subrutine calls together with the parameters The compiler was merely a linker and a loader Followed by the A-1, A-2, A-3 ARITH-MATIC, MATH-MATIC, FLOW-MATIC

13 Fortran First complete compiler John W. Backus, 1953, IBM IBM 704 mainframe Mathematical FORmula TRANslating System IBM 360 Constructs of Fortran DO, GOTO, IF, SUBRUTINE, CALL Numeric processing Programs can be parallelized Followed by the imperative familiy C, Pascal, Modula Fortran II, Fortran 77, Fortran III, Fortran 90, Fortran 95, Fortran 2003,...

14 FLOW-MATIC Bussiness Language version 0, or, B-0. UNIVAC I at Remington Rand Grace Hopper in Bussiness does not like formulas English language Hopper team developed compiler by First language that made a clear distinction between the data definition section and the code section of the Strong influence on the development of the programming language COBOL.

15 Information Processing Language Information Processing Language (IPL) Allen Newell, Cliff Shaw and Herbert Simon Rand Corporation in Assembly language - operations manipulate lists IPL computer Set of symbols, set of cells, set of primitive functions Functions defined on the cells and lists primitive PL run-time environment AI language Abstract and suitable for expressing AI programs Programs are not efficient

16 Algol C.A.R. Hoare: "Here is a language so far ahead of its time that it was not only an improvement on its predecessors but also on nearly all its successors." Developed in ETH Zuerich, Team of computer scientists from Europe and US Allan J. Perlis, Peter Naur, John McCarthy, and others Originally: Algebraic Language, or, IAL Avoided problems percived in FORTRAN Contributions John Backus developed BNF to specify ALGOL 58 Formal semantics, two parameter passing methods: cbv and cbr, code blocks, nested functions, lexical scope Imperative effect of cbr to lambda calculus studied Influence: Pascal, C, Modula, Java,...

17 Lisp Developed by John McCarthy at MIT, 1958 Lisp is based on lambda calculus Alonzo Church in 1930 ble Church's paper on undecidable problem Strongly influenced by IPL Lists used for representation of programs and data New concepts Automatic storage management, dynamic typing, selfhosting compiler, and others. AI language Second-oldest programming language that is still in use Common Lisp and Scheme.

18 Cobol Designed by CODASYL, 1959 Conference/Committee on Data Systems Languages Previous work of Grace Murray Hopper Programming language for bussiness applications Imperative and procedural Since 2002, object-oriented A compiled English-like programming language Awkward syntax Cobol pograms work today! Syntax has been changed

19 C Programming Language Dennis Ritchie, Bell Laboratories, 1972 C designed for Language B, based on BCPL Language constructs Algol family Still one of best languages (C++ =? C + object illusion) Close to hardware, system programming Arrays and references are closely related E1[E2] = ]*((E1)+(E2)) Adress arithmetic Ritchie wrote: C is quirky, flawed, and a tremendous success.

20 Pascal Niklaus Wirth, ETH Zürich, 1970 Very popular in Europa Structred programming language Algol family Data structures, pointers, arrays, variable records,... Many implementations VAX Pascal, Turbo Pascal, Delphi: nice programming environment Modula-2, Modula-3, Oberon

21 Language sequences Lisp Algol 60 Algol 68 Pascal ML Modula

22 Functional languages Rooted in logic Lambda calculus, 1930, Alonzo Church LISP John McCarthy Implementation of lambda calculus Meta-Language ML, Rob Milner Functional languages are more appropriate for teaching? Strong typing Program is proof Elements of declarative programming USA

23 History of ML Logic for computable functions (LCF) Robin Milner, Dana Scott Stanford , Edinburgh Meta-language for LCF system Automatization of logic reasoning Proofs Type systems Notation for programs Higher-order functions Programs that search for proof

24 Object-Oriented Languages First OO language is Simula. Simulation programming environment Smalltalk is one of the most famous OO languages Adele Goldberg, Xerox, Palo Alto Everything is object! Every object belongs to one class Class is prototype object Class is object! Complex inheritance hierarchies C++, Java, Objective C,... Java J.Gosling, B.Joy, G.Steele, G.Bracha The Java Language Specification

25 Script languages Web programming languages V zadnjih letih se je pojavila množica jezikov, za delo na Web strežnikih JSP, PhP, JavaScript, ASP, Reseources of Web server System programming languages Strong ties to OS C + Awk, Perl, Python System integration languages

26 High-level languages Information systems 4GL, PL/SQL, SQL3 UML (specifikacije) Electronics VHDL, EDIF,...

27 Prolog Programming in Logic, Robert Kowalski Predicate calculus Horn clauses Unification, resolution Strong, simple and abstract language Back-tracking Declarative and procedural semantics of Prologa Operator CUT (!) Database programming languages Datalog Sicstus, SB Prolog, SWI Prolog,

28 Concepts in programming languages Programming language is programming tool, defined in the form of language, that is used for design and implementation of computer programs. Concepts of programming languages are abstractions used for representation of structure and behaviour of modelled systems.

29 Abstraction In Philosophy Specific operation of the intellect consisting in detaching and retaining some property from a thing Aristotel Constructive mental process associated with the relation between forms (ideas) and concrete objects Human mind actively abstracts or extracts forms from the objects in which they are realized St. Thomas Aquinas Two kinds of abstractions Mind joins properties that are separate from each other Mind separates properties that are one

30 Concepts in programming languages Abstractions integrated into the language Function, object, method, class, abstract class,..., classification, specialization, aggregation,... Abstractions define language model Imperative languages: variables, loops, procedures,... Funtional languages: functions Object languages: object and classes

31 Classifications of PL concepts Algorithmic and data abstractions Algorithmic abstractions Itaration statements, patterns, recursion,... Data abstractions N-tuples, lists, recursive data structures Language and implementation concepts Language abstractions Functions, objects, methods, inheritance,... Implementation abstractions Memory management, parameter passing,...

32 Implementation concepts We learn about the implementation of PL constructs Representation of variables, data structures,... Memory management Memory organization Garbage collection Implementation of PL concepts Functions in C, Java, Ocaml,... Parameters in C, Java, Ocaml,... Classes in Java, OCaml,...

33 Properties of abstractions in PL Closer to hardware, more simple languages Simple abstractions: Numbers, characters, loops, routines,... Higher abstractions: Objects, modules,... Higher level of abstraction in PL: More directed language Very general abstractions - more specific language General programming language is in the middle: Wide applicability General-purpose PL Very complex languages

34 Abstractions Study of abstractions can improve learning process COMMUNICATIONS OF THE ACM April 2007/Vol. 50, No. 4 IS ABSTRACTION THE KEY TO COMPUTING?

35

36 Why to study concepts in PL? We learn about the possible ways of expressing ideas. We learn how to use given PL abstractions correctly. You have to know the tool It is good to have formal background It is good to have experiences with using tools

37 Meta-Language Meta Language (ML) Developed unintentionally while working on system for automatic theorem proving based on LCF Logic of computable functions. LCF is a version of lambda calculus Initially at Edinburg University Later in AI group of Stanford University Project leader was Robin Milner. Meta-Language was used as language for expressing mathematical proofs They would change the files with proofs to obtain better proof

38 Meta-Language Success story from functional branch of programming languages Standard ML, SML/NJ, Alice ML, Ocaml, Moscow ML, Mlton, MLKit, SML.NET,... Research related to ML Hindley-Milner type-checking algorithm Polimorfic lambda calculus (System F, Girard)

39 Lambda calculus Lambda calculus is the foundamental formalism for studying programming languages Theory of programming languages Using rule-based reasoning for: deriving expression types, evaluation of expressions, Prooving the properties of language, etc. Static and dynamic semantics of PL Prooving the properties of languages (determinism, strict typing, termination, etc.). Labda calculus is topic of one lecture

40 Objective Caml Objective Caml is reference language Caml core is pure lambda calculus. Theoretically well-studied language. Caml has strong typing. Imperative constructs. Parametric polymorphism Nice object model Modules and functors Ocaml offers more than one programming models Imperative + functional + object-oriented + modular programming model

41 communications of the acm november vo l. 5 4 n o. 1 1

42

43 Who uses OCaml Facebook Jane Street Bloomberg, Citrix, See:

44 Comparisons of PL Codeval comparison A Comparison of Programming Languages in Economics In-Deman Programming languages The Computer Language Benchmarks Game Githut TIOBE Index

45

46

47

48

49

50 A Comparison of Programming Languages in Economics, Aruoba and Fernandez-Villaverde, 2014

51

52

53

54

55 Kotkin: Java reconsidered Erlang: Functional programming for real-time systems Go: Simple and dynamic OCaml: Complex data hierarchy juggler TypeScript: JavaScript you ll like Rust: Safe and usable systems language...

56 The Computer Language Benchmarks Game 33 languages, 4 systems, 13 test programs

57

58 High-level programming languages can be very efficient Java and Ocaml are efficient languages

59

60

61 Energy Efficiency across Programming Languages: How does Energy, Time and Memory Relate?

62 Energy Efficiency across Programming Languages: How does Energy, Time and Memory Relate?

63 Speed, size and memory usage of PL 429 programs 13 test programs 33 PL Experiment: Guillaume Marceau

64

65 githut Programming languages on github, M active repositories Parameters No. of projects on github No. of push operations No. of push/repository operations No. of fork operations No. of opened issues No. of watchers 65

66

67

68 TIOBE Indeks: Indeks based on: Web search engines: Google, Bing, Yahoo!, Wikipedia, Amazon, YouTube, Baidu TIOBE index is NOT: About best PL About the most used PL 68

69

70

71

72

73 Aims of course Concepts of programming languages Language is»conceptual universe (Perlis) Framework for solving problems Usefull concepts and constructs of PLs Learning more than one PL It is good to know the history! Learning concepts from sources Efficient usage of PL constructs 73

74 Methods Lambda calculus Formal foundation Basic principles of procedural PL Lisp: first programming language based on LC ML Mathematical foundations Strong typing Includes most PL constructs Java + C Languages to compare ML! C is still the most popular language Java uses clean object-oriented model Strong typing and dynamic typing 74

75 Methods First classification = language model Functional, imperative, object, module Some concepts will be put forward Functions, parameters, types, scope, control, data abstractions, inheritancem polimorphism, memory We will see diferent approaches Languages used: C, ML, Java Sometimes: Pascal, Fortran, C++, Ada Comparison of PL concepts We know what we can use Concepts can also be very different 75

76 Method Learning about PL constructs and implementation Every construct has its price It always good to know what is happening»below«efficient use of constructs Many times it is neccessary to know implementation of concepts Memory management Representation of data structures Implementation of functions and recursion Dynamic aspects of languages 76

77 What is happening in PL area? Trendy applications Complex programming systems Telecommunications Parallel programming Data mining/data science Supercomputers Visual/dataflow programming Artificial intelligence 77

78 What is happening in PL area? Classical high-level PL Java, C++, C, C#, Script/system languages Python, Perl, Lua, Rust,... Abstract but efficient PL Scala, Swift, Ruby, Go,. Increased use of functional languages Haskell, F#, Ocaml, Erlang, ML,... Increased use of functional concepts Java, C++, Scala, Ruby, Python,... Data programming languages R, Julia, Mathlab, SAS... 78

79 What is happening in PL area? Java is replacing C and C++? C, C++ is replacing Java? Python as the first language? Lisp/Schema still first language? C is coming back? Practical languages Python in schools? Strong programming environments Strong open-source support 79

80 What is happening in PL area? Research trends Strong typing, dynamic typing Dynamic and JIT optimization Compilers and multicore programming challenge Parallel programming Program graph analysis for parallelization Meta-programming 80

81 What is happening in PL area? Programming languages for target systems Mobile phones, ipad, El.machines, TV, car, washing machine, Concurrent PL Erlang, Concurrent ML, E, CAL,... Dataflow programming Multi-processor, multi-threaded prgramming 81

82 What is happening in PL area? More formal analysis used Type-checking, static and dynamic typing, program analysers, diagnostics, Abstract VM Additional level of abstraction: Virtual Machine Java VM, Erlang VM (BEAM),... Portability Meta-pogramming languages Coq, Isabelle, Twelf Languages used to analyse, test and implement other programming languages 82

83 What to learn? Most commonly used PLs C, C++, Java, Python Concepts of PLs Important implementation ideas New trends New languages: R, VimL, Go, Swift, Scala Functional constructs: Haskell, Ruby, C++, Java Design decisions trade-offs Functional vs. imperative, modular vs. object-oriented,... 83