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Programming Paradigms Vitaly Shmatikov

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Reading Assignment Mitchell, Chapter 2.1

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What Is a Programming Language? Formal notation for specifying computations, independent of a specific machine Example: a factorial function takes a single non-negative integer argument and computes a positive integer result Mathematically, written as fact: nat  nat Set of imperative commands used to direct computer to do something useful Print to an output device: printf(“hello world\n”); What mathematical function is “computed” by printf?

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Partial and Total Functions Value of an expression may be undefined Undefined operation, e.g., division by zero 3/0 has no value Implementation may halt with error condition Nontermination f(x) = if x=0 then 1 else f(x-2) This is a partial function: not defined on all arguments Cannot be detected by inspecting expression (why?) These two cases are “mathematically” equivalent, but operationally different (why?)

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Partial and Total: Definitions Total function f:AB is a subset f  AB with  xA, there is some yB with x,y  f (total) If x,y  f and x,z  f then y=z (single-valued) Partial function f:AB is a subset f  AB with If x,y  f and x,z  f then y=z (single-valued) Programs define partial functions for two reasons What are these reasons?

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Computability Function f is computable if some program P computes it For any input x, the computation P(x) halts with output f(x) Partial recursive functions: partial functions (int to int) that are computable

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Halting Problem Ettore Bugatti: "I make my cars to go, not to stop"

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Halting Function Decide whether program halts on input Given program P and input x to P, Halt(P,x) = Fact: There is no program for Halt

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Unsolvability of the Halting Problem Suppose P solves variant of halting problem On input Q, assume P(Q) = Build program D D(Q) = If D(D) halts, then D(D) runs forever If D(D) runs forever, then D(D) halts Contradiction! Thus P cannot exist.

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Main Points About Computability Some functions are computable, some are not Example: halting problem Programming language implementation Can report error if program result is undefined due to an undefined basic operation (e.g., division by zero) Cannot report error if program will not terminate

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Computation Rules The factorial function type declaration does not convey how the computation is to proceed We also need a computation rule fact (0) = 1 fact (n) = n * fact(n-1) This notation is more computationally oriented and can almost be executed by a machine

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Factorial Functions C, C++, Java: int fact (int n) { return (n == 0) ? 1 : n * fact (n-1); } Scheme: (define fact (lambda (n) (if (= n 0) 1 (* n (fact (- n 1)))))) ML: fun fact n = if n=0 then 1 else n*fact(n-1); Haskell: fact :: Integer->Integer fact 0 = 1 fact n = n*fact(n-1)

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Principal Paradigms Imperative / Procedural Functional / Applicative Object-Oriented Concurrent Logic Scripting In reality, very few languages are “pure” Most combine features of different paradigms

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Where Do Paradigms Come From? Paradigms emerge as the result of social processes in which people develop ideas and create principles and practices that embody those ideas Thomas Kuhn. “The Structure of Scientific Revolutions.” Programming paradigms are the result of people’s ideas about how programs should be constructed … and formal linguistic mechanisms for expressing them … and software engineering principles and practices for using the resulting programming language to solve problems

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Imperative Paradigm Imperative (procedural) programs consists of actions to effect state change, principally through assignment operations or side effects Fortran, Algol, Cobol, PL/I, Pascal, Modula-2, Ada, C Why does imperative programming dominate in practice? OO programming is not always imperative, but most OO languages have been imperative Simula, Smalltalk, C++, Modula-3, Java Notable exception: CLOS (Common Lisp Object System)

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Functional and Logic Paradigms Focuses on function evaluation; avoids updates, assignment, mutable state, side effects Not all functional languages are “pure” In practice, rely on non-pure functions for input/output and some permit assignment-like operators E.g., (set! x 1) in Scheme Logic programming is based on predicate logic Targeted at theorem-proving languages, automated reasoning, database applications Recent trend: declarative programming

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Concurrent and Scripting Languages Concurrent programming cuts across imperative, object-oriented, and functional paradigms Scripting is a very “high” level of programming Rapid development; glue together different programs Often dynamically typed, with only int, float, string, and array as the data types; no user-defined types Weakly typed: a variable ‘x’ can be assigned a value of any type at any time during execution Very popular in Web development Especially scripting active Web pages

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Unifying Concepts Unifying language concepts Types (both built-in and user-defined) Specify constraints on functions and data Static vs. dynamic typing Expressions (e.g., arithmetic, boolean, strings) Functions/procedures Commands We will study how these are defined syntactically, used semantically, and implemented pragmatically

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Design Choices C: Efficient imperative programming with static types C++: Object-oriented programming with static types and ad hoc, subtype and parametric polymorphism Java: Imperative, object-oriented, and concurrent programming with static types and garbage collection Scheme: Lexically scoped, applicative-style recursive programming with dynamic types Standard ML: Practical functional programming with strict (eager) evaluation and polymorphic type inference Haskell: Pure functional programming with non-strict (lazy) evaluation.

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Abstraction and Modularization Re-use, sharing, extension of code are critically important in software engineering Big idea: detect errors at compile-time, not when program is executed Type definitions and declarations Define intent for both functions/procedures and data Abstract data types (ADT) Access to local data only via a well-defined interface Lexical scope

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Static vs. Dynamic Typing Static typing Common in compiled languages, considered “safer” Type of each variable determined at compile-time; constrains the set of values it can hold at run-time Dynamic typing Common in interpreted languages Types are associated with a variable at run-time; may change dynamically to conform to the type of the value currently referenced by the variable Type errors not detected until a piece of code is executed

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Billion-Dollar Mistake Failed launch of Ariane 5 rocket (1996) $500 million payload; $7 billion spent on development Cause: software error in inertial reference system Re-used Ariane 4 code, but flight path was different 64-bit floating point number related to horizontal velocity converted to 16-bit signed integer; the number was larger than 32,767; inertial guidance crashed

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Program Correctness Assert formal correctness statements about critical parts of a program and reason effectively A program is intended to carry out a specific computation, but a programmer can fail to adequately address all data value ranges, input conditions, system resource constraints, memory limitations, etc. Language features and their interaction should be clearly specified and understandable If you do not or can not clearly understand the semantics of the language, your ability to accurately predict the behavior of your program is limited

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Language Translation Native-code compiler: produces machine code Compiled languages: Fortran, C, C++, SML … Interpreter: translates into internal form and immediately executes (read-eval-print loop) Interpreted languages: Scheme, Haskell, Python … Byte-code compiler: produces portable bytecode, which is executed on virtual machine (e.g., Java) Hybrid approaches Source-to-source translation (early C++  Ccompile) Just-in-time Java compilers convert bytecode into native machine code when first executed

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Language Compilation Compiler: program that translates a source language into a target language Target language is often, but not always, the assembly language for a particular machine

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Checks During Compilation Syntactically invalid constructs Invalid type conversions A value is used in the “wrong” context, e.g., assigning a float to an int Static determination of type information is also used to generate more efficient code Know what kind of values will be stored in a given memory region during program execution Some programmer logic errors Can be subtle: if (a = b) … instead of if (a == b) …

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Compilation Process

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Phases of Compilation Preprocessing: conditional macro text substitution Lexical analysis: convert keywords, identifiers, constants into a sequence of tokens Syntactic analysis: check that token sequence is syntactically correct Generate abstract syntax trees (AST), check types Intermediate code generation: “walk” the ASTs and generate intermediate code Apply optimizations to produce efficient code Final code generation: produce machine code

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Language Interpretation Read-eval-print loop Read in an expression, translate into internal form Evaluate internal form This requires an abstract machine and a “run-time” component (usually a compiled program that runs on the native machine) Print the result of evaluation Loop back to read the next expression

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Bytecode Compilation Combine compilation with interpretation Idea: remove inefficiencies of read-eval-print loop Bytecodes are conceptually similar to real machine opcodes, but they represent compiled instructions to a virtual machine instead of a real machine Source code statically compiled into a set of bytecodes Bytecode interpreter implements the virtual machine In what way are bytecodes “better” then real opcodes?

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Binding Binding = association between an object and a property of that object Example: a variable and its type Example: a variable and its value A language element is bound to a property at the time that property is defined for it Early binding takes place at compile-time Late binding takes place at run-time

Теги Programming paradigms

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