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Overview
Chapter 1
Overview
A good programming language is a conceptual
universe for thinking about programming.
A. Perlis
Copyright © 2006 The McGraw-Hill Companies, Inc.
1.1
1.2
1.3
1.4
1.5
Principles
Paradigms
Special Topics
A Brief History
On Language Design
1.5.1 Design Constraints
1.5.2 Outcomes and Goals
1.6 Compilers, Interpreters, and Virtual Machines
Copyright © 2006 The McGraw-Hill Companies, Inc.
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Programming languages have several
properties, including
◦ Syntax
◦ Names & types
◦ Semantics
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Language designers define these properties
Language users must understand them
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Syntax describes
◦ Legal statements
◦ Legal programs
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Syntax defines the form of a correct program –
doesn’t say anything about program meaning
Who needs to know PL syntax?
◦ Programmers: how to write a correct program
◦ Translators: how to recognize a correct program
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Various kinds of entities in a program have
names:
variables, functions, parameters, classes,
objects, …
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Named entities are bound in a running
program to:
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Scope
Visibility
Type
Lifetime
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A type is a collection of values and a
collection of operations on those values.
◦ Simple types: numbers, characters, booleans, …
◦ Structured types: Strings, lists, arrays, hash
tables, …
A language’s type system
◦ Defines legal operations
◦ Defines type errors
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A program’s meaning is defined by its
semantics.
In studying semantics, we ask questions like:
◦ When a program is running, what happens to the
values of the variables?
◦ What does each statement mean?
◦ What underlying model governs the run-time
behavior of a function call?
◦ …
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A programming paradigm is a pattern or
framework for problem-solving
Languages typically identify primarily with
one paradigm, but may have aspects of
several
Common paradigms can be grouped together
according to whether they have imperative
characteristics or declarative characteristics.
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Imperative languages:
◦ Pure Imperative (von Neumann languages); e.g., C,
Pascal, early versions of Fortran & Ada, …
◦ Object-oriented; e.g., C++, Java, Smalltalk
◦ Most of what we’ll study focuses on these
languages
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Declarative languages
◦ Functional
 Lisp, Scheme, ML, Haskell, …
◦ Logic
 Prolog, SQL, …
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Follows the classic von Neumann-Eckert model
of computation:
◦ Program and data are indistinguishable in memory
◦ Program = a sequence of commands
◦ Programs work by changing values of memory
variables
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Large programs use procedural abstraction as
a way to organize individual imperative
statements.
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OO languages share many characteristics with
the pure imperative languages
Programs consist of a collection of objects
that communicate via “messages” that modify
object state
◦ Messages are imperative
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OO languages are characterized by
◦ Encapsulation
◦ Inheritance
◦ Polymorphism
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Functional programming models a computation
as a function that maps inputs to outputs.
◦ Input = domain
◦ Output = range
Functional languages are characterized by:
◦ Functional composition
◦ Recursion
Example functional languages:
◦ Lisp, Scheme, ML, Haskell, …
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Logic programming declares what outcome
the program should accomplish, rather
than how it should be accomplished.
Based on predicate logic
Rule-based
When studying logic programming we see:
◦ Programs as sets of constraints on a problem
◦ Find values that satisfy all constraints
Example logic programming languages:
Prolog
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Event handling
◦ E.g., GUIs, home security systems, monitoring
systems of various kinds
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Concurrency
◦ e.g., Client-server programs, rendering (in
computer graphics)
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Correctness
◦ Can we prove that a program does what it is
supposed to do under all circumstances?
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How and when did programming languages
evolve?
What communities have developed and
used them?
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Artificial Intelligence
Computer Science Education
Science and Engineering
Information Systems
Systems and Networks
World Wide Web
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1.5.1 – Design Constraints
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Computer architecture
Technical setting (domain of applications)
Standards
Legacy systems
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Key characteristics:
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Simplicity, readability and writability
Clarity about binding
Reliability
Support
Abstraction
Orthogonality
Efficient implementation
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Early languages focused on efficiency
◦ Time
◦ Space
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Today, programs that are easy to read and
easy to write are most likely to be successful
Promoted by simplicity of the language.
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Easy to learn
◦ Don’t include too many features
◦ Don’t make it too complex
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Simple conceptual model of semantics.
Uniformity: Similar syntax => similar
semantics.
Lexical and syntactic conventions:
◦ descriptive identifier names, blocking of
compound statements
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A language element is bound to a property at
the time that property is defined for it.
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So a binding is the association between an
object and a property of that object; the binding
time should be clearly understood.
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Examples:
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variable and type: program writing time or execution
time?
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variable and value: program writing time and execution
time
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language operator to machine language instruction: ??
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Major binding times
◦ Language definition time
◦ Language implementation time
◦ Program writing time
◦ Compile time
◦ Load time
◦ Execution time
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In general,
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Early v late: efficiency versus flexibility
◦ Early binding takes place at or before compile-time
◦ Late binding takes place at load time or run time
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A language is reliable if:
◦ Program behavior is the same on different
platforms
 E.g., early versions of Fortran weren’t
◦ Type errors are detected
 E.g., C vs Haskell or ML
◦ Good exception-handling facilities
 E.g., C vs Java
◦ Memory leaks are prevented
 E.g., C/C++ vs Java
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Good texts and tutorials
Wide community of users
Integrated with development environments
(IDEs)
Accessible compiler/interpreters (public
domain)
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Data
◦ Programmer-defined types/classes
◦ Class libraries
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Procedural
◦ Programmer-defined functions
◦ Standard function libraries
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Supports code reuse; simplifies the
programming process.
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A language is orthogonal if it is built on a
small, mutually independent set of primitive
operations.
◦ You can use one feature without worrying about
how it affects others
◦ Rules don’t have exceptions;
◦ Context doesn’t affect the behavior of a language
feature (e.g., a reserved word doesn’t have
different meanings based on where it’s used).
◦ Things that are syntactically similar have similar
meaning.
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Rule exceptions:
◦ C functions can return a struct, but not an array.
Orthogonality => return value can be any type.
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Syntactic exceptions
◦ In Fortran, an identifier can indicate the type of the
variable; this could be considered non-orthogonal
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If A = B; and A = (B); acceptable,
should (A) = B; be allowed?
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Embedded systems
◦ Real-time responsiveness (e.g., navigation)
◦ Failures of early Ada implementations – real time?
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Corporate database applications
◦ Efficient search and updating
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Ability to implement the language efficiently
◦ Characteristics of Lisp didn’t match the
architectures of early computers
◦ Characteristics of Algol made it difficult to build
efficient translators.
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Compiler – produces machine code
Interpreter – executes instructions directly
 Example compiled languages:
◦ Fortran, Cobol, C, C++
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Example interpreted languages:
◦ Scheme, Haskell, Python
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Hybrid compilation/interpretation: Java
◦ The Java Virtual Machine (JVM)
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Just-in-time (JIT) compilation: C#, some Java
◦ Compiled to intermediate code, machine code produced
just before execution
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Translation/Execution – Compiler
se
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Translate source code program into object
code (machine language).
Object code is linked to libraries, other
modules, to generate an executable object
code module
Object code can be executed repeatedly
without repeating the compilation process.
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Translation/Execution – Interpreter
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No object code file generated.
Interpretive routines
◦ Examine the program. When an action is
recognized, do it (by calling one of the
routines).
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Slower execution (than with compilation):
lexical, syntax, type/semantic analysis
must be performed every time it runs
Better interactive development
environment.
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Some languages (e.g., Java) are compiled to
a machine code (byte code) that runs on a
virtual machine (the JVM).
To run Java programs install a JVM for your
machine that interprets the byte code.
Benefit: “compile once, run anywhere” – as
long as “anywhere” has a JVM. Compiled
languages need to be compiled for a
specific platform
Disdadvantage: slow
Solution: JIT compilers
Copyright © 2006 The McGraw-Hill Companies, Inc.
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Programming language principles
◦ Grammars, syntax, semantics
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What makes a language successful?
 Reliable, readable, writeable
 Supported by simplicity, orthogonality, efficiency,
support, …
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Paradigms
◦ Imperative, object-oriented, functional, logic
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Language implementation
◦ Compilers & interpreters & hybrid systems
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