01 preliminaries

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CSI 3125, Preliminaries, page 1

Preliminaries

Programming languages and the

process of programming.

Criteria for the design and evaluation

of programming languages

Basic ideas of programming language

implementations.

What we will discuss:


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Programming languages

and the process of programming

Points to discuss:

Programming means more thancoding.

Why study programming languages?

Programming language paradigmsand applications.


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Programming means much more than

coding in a programming language

Before coding begins, you analyze the problem,

design (or borrow) an algorithm, analyze the

cost of the solution.

After all coding has been done, you have tomaintain the program.

Programming languages are used to instruct

computers.

What do we communicate to computers?

How do computers talk back to us?


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Programming means more than coding (2)

How do programming languages differ

from natural languages? Would talking to

computers (instructing them) in human

languages be preferable?

What makes someone a good

programmer?

Should a good programmer know morethan one programming language?


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Why should we study

programming languages?

To understand better the connection between

algorithms and programs.

To be able to look for general, language-

independent solutions.

To have a choice of programming tools that

best match the task at hand:

identify subtasks and apply to each of themthe bestlanguage, using the full expressive

power of each language.


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Why should we study

programming languages? (2)

To appreciate the workings of a computer

equipped with a programming languageby

knowing how languages are implemented.

To learn new programming languages easilyand to know how to design new formal

languages (for example, input data formats).

To see how a language may influence thediscipline of computing and strengthen good

software engineering practice.


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The many classes

of programming languages:

programming language paradigms

Every programming language supports a

slightly different or dramatically differentstyle of problem solving.

The same computation can be

expressed in various languages, andthen run on the same computer.


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Programming languages

classified by paradigm

Imperative: howdo we solve a problem (whatsteps does a solution have)?

Logic-based: whatdo we do to solve a problem?

(The language decides howto do it.) Functional: what simple operations can be

applied to solving a problem, how are theymutually related, and how can they be combined?

Object-oriented: what objects play roles in aproblem, what can they do, and how do theyinteract to solve the problem?


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Classification by generality of use

General-purpose programming languages

(most of the known languages are in this

category);

Specialized programming languages

(for example, database languages, vector-

processing languages, report generation

languages, scripting languages, and more).


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Classification by complication,

abstraction, level

Low-level languages (machine languages,assembly languages).

High-level languages (most of the well-known languages belong in this category).

Very high-level languages (Prolog issometimes listed in this category, andsome specialized languages).

Beyond programming languages: Programming environments, software

development tools and workbenches.


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Classification by area of application

Data processing (also known as "businessapplications").

Now made largely unnecessary, since we havedatabases and other business-related

packages, such as spreadsheets, and special-purpose software.

Scientific computing (this includes engineering).

Today this has been changed by new hardware

designs such as supercomputers or vectorcomputers, and specialized computing devices.


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Classification by area of application (2)

Artificial intelligence and other applicationsnot in the computer science mainstream.

This might include educational softwareand games.

New hardware (so far mostly simulated)such as connection machines and neuralnetworks.

"In-house" computing applications.

compiler construction, systemsprogramming, GUI, API, and so on.


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Criteria for the design and evaluation

of programming languages

Points to discuss:

Readability

Writability

Reliability

Cost


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Readability

This is subjective, but very important.

Language readability is essential because

of software engineering practices, and in

particular the needs of software evolution

and maintenance.Abstractionsupport for generality of

programs: procedural abstraction, data

abstraction.

Absence of ambiguity (and absence oftoo many coding choices, like having five

different loop constructs).


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Readability (2)

Orthogonality: there are no restrictions oncombinations of primitive language concepts.(It is easier to detect lackof orthogonality.)

For example, can everything have a value?

Can an array group things of every kind?

......

More orthogonality = fewer special cases inthe language.

This may be carried too far (as in Algol 68).


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Readability (3)

Expressivity of control and data structures. what is better (easier to read, maintain and so on):

a longer program made of simple elements?

a shorter program built out of complex,

specialized constructions? Examples of high expressive power: recursion,

built-in backtracking (as in Prolog), search indatabase languages.

Examples of low expressive power: instructions inmachine or assembly languages.

Appearance: syntax, including comments.


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Writability

Abstraction and simplicity: once more, subjective. Pascal has always been considered simple, Ada

complicated

Basic is very simple

Prolog is conceptually simple, but may be difficultto learn.

is C++ simple? is Java?

Expressivity again.

Modularity and tools for modularization, support forintegrated programming environments.


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Reliability and Cost

Reliability.

Safety for the programmer (type checking, errorand exception handling, unambiguous names).

Cost.

Development time (ease of programming,

availability of shared code).

Efficiency of implementation: how easy it is to builda language processor (Algol 68 is a known failure,

Ada almost a failure; Pascal, C, C++ and Java are

notable successes). Translation time and the quality of object code.

Portability and standardization.


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Implementing programming languages

Points to discuss:

Language processors,virtual machines

Models of implementation

Compilation and execution


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Language processors

A processor for language L is any device(hardware or software) that understands andcan execute programs in language L.

Translation is a process of mapping a program

in the source language into the target language,while preserving the meaning or function of thesource program.

The target language may be directly executable

on the computer or (more often) may have tobe translated againinto an even lower-levellanguage.


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Virtual machines

A virtual machine is a software realization

(simulation) of a language processor.

Programming directly for hardware is very

difficultwe usually "cover" hardware with

layers of software.

A layer may be shared by several language

processors, each building its own virtual

machine on top of this layer.


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Examples of shared layers

All language processors require

support for input/output.

All language processors eventually

must do some calculations, that is,

use the CPU.


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Virtual machines

We normally have hierarchies of virtual

machines:

at the bottom, hardware;

at the top, languages close to the

programmer's natural way of thinking.

Each layer is expressed only in terms of

theprevious layerthis ensures proper

abstraction.


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A generic hierarchy

of virtual machines

Layer 0: hardware

Layer 1: microcode

Layer 2: machine language

Layer 3: system routines

Layer 4: machine-independent code

Layer 5: high-level language (or assembler)

Layer 6: application program

Layer 7: input data [this is also a language!]


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Virtual machinesexamples

Layer 0: IBM Netvista with Intel Pentium 4, 2GHzLayer 1: IBM Intel machine language

Layer 2: Windows XP

Layer 3: Java byte-code

Layer 4: Java 2.0 (code developed in JRE 1.4.0)

Layer 5: smart comparator of C++ programs,written in Java

Layer 6: two C++ programs to comparefor similarities


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Virtual machinesexamples (2)

Layer 0: IBM Netvista with Intel Pentium 4, 2GHz

Layer 1: IBM Intel machine language

Layer 2: Windows NT 4.0

Layer 3: Java byte-code

Layer 4: JDK 1.2

Layer 5: a Java implementation of Prolog

Layer 6: a Prolog implementation of mySQL

Layer 7: a database schema defined and created

Layer 8: records for insertion into the database


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Models of implementation

Compilation: translate the program into an equivalent

form in a lower-layer virtual machinelanguage;

execute later. Interpretation:

divide the program up into small(syntactically meaningful) fragments;

in a loop, translate and execute eachfragment immediately.


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Models of implementation (2)

Pure compilation and pure interpretation areseldom use. Normally, an implementationemploys a mix of these models.

For example: compile Java intobytecodes, then interpret bytecodes.

We consider a language processor aninterpreter if it has "more interpretation than

compilation". We consider a processor acompiler if there is more of compilation.


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Models of implementation (3)

Some languages are better interpreted, forexample interactively used Prolog or Lisp.

Some languages are better compiled, forexample, C++, Java.

There can also be compiled Prolog or Lisp:

an interpretive top-level loop handles userinteraction.

Predicates of functions are compiled into anoptimized form which is then interpreted.


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CSI 3125 Preliminaries page 30

Compilation and execution

Output DataInput Data

Target Program

Abstract Program

(Optimized)

Parse TreeSymbol Table

Source program

Code

OptimizationSemantic

Analysis

Loader / LinkerCode

Generation

Computer

Lexical Analysis

(scanning)

Syntactic Analysis

(parsing)

compiler

Token Sequence

Abstract Program

(Intermediate code)

Object Program

(Native Code)

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