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Concepts of Programming Languages Eleventh Edition Global

Chapter 1 begins with a rationale for studying programming languages It then discusses the criteria used for evaluating programming languages and language constructs The primary influences on language design common design trade-offs and the basic approaches to implementation are also examined

PDF	Principles of Programming Languages Version 10

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The A-Z of Programming Languages

for many of the advanced features in other programming languages Ada was one of the ﬁrst widely-used languages to have a language construct representing an abstraction (a package) an abstract data type (a private type) multi-threading (tasks) generic templates exception handling strongly-typed separate compilation subprogram inlining etc

What is Chapter 1 of programming languages?
Chapter 1 begins with a rationale for studying programming languages. It then discusses the criteria used for evaluating programming languages and language constructs. The primary influences on language design, common design trade- offs, and the basic approaches to implementation are also examined.
What are the different approaches to implementing programming languages?
Three different approaches to implementing programming languages are introduced in Chapter 1: compilation, pure interpretation, and hybrid implementation. The compilation approach uses a program called a compiler, which translates programs written in a high-level programming language into machine code.
What is a good book about programming languages?
The paper “Early Development of Programming Languages” (Knuth and Pardo, 1977), which is part of the Encyclopedia of Computer Science and Technology, is an excellent 85-page work that details the development of languages up to and including Fortran. The paper includes example programs to demonstrate the features of many of those languages.

Introduction

In this book, our goal is to study the fundamental concepts in programming languages, as opposed to learning a range of speci c languages. Languages are easy to learn, it is the concepts behind them that are di cult. The basic features we study in turn in-clude higher-order functions, data structures in the form of records and variants, mutable sta

The FbDK

Complementing the book is the F[ Development Kit, FbDK. It is a set of OCaml utilities and interpreters for designing and experimenting with the toy F[ and F[SR languages de ned in the book. It is available from the book homepage at http://pl.cs.jhu.edu/ pl/book. 1 pl.cs.jhu.edu

Background Needed

The book assumes familiarity with the basics of OCaml, including the module system (but not the objects, the \\O" in OCaml). Beyond that there is no absolute prerequisite, but knowledge of C, C++, and Java is helpful because many of the topics in this book are implemented in these languages. The compiler presented in chapter 8 produces C code as its

2.1 A First Look at Operational Semantics

The syntax of a programming language is the set of rules governing the formation of expressions in the language. The semantics of a programming language is the meaning of those expressions. There are several forms of language semantics. Axiomatic semantics is a set of ax-iomatic truths in a programming language. Denotational semantics involves mode

2.2 BNF grammars and Syntax

Before getting into meaning we need to take a step back and rst precisely de ne language syntax. This is done with formal grammars. Backus-Naur Form (BNF) is a standard grammar formalism for de ning language syntax. You could well be familiar with BNF since it is often taught in introductory courses, but if not we provide a brief overview. All BNF

j hform ni

where each \\form" above describes a particular language form { that is, a string of terminals and non-terminals. A term in the language is a string of terminals which matches the description of one of these rules (traditionally the rst). For example, consider the language Sheep. Let fSg be the set of nonterminals, fa; bg be the set of terminals, an

S ::= b j Sa

Note that this is a recursive de nition. Examples of terms in Sheep are b; ba; baa; baaa; baaaa; : : : That is, any string starting with the character b and followed by zero or more a characters is a term in Sheep. The following are examples that are not terms in SHEEP: a: Terms in Sheep must start with a b. bbaaa: Sheep does not allow multiple b c

S a

The above syntax diagram describes all terms of the Sheep language. To generate a form of S, one starts at the left side of the diagram and moves until one reaches the right. The rectangular nodes represent non-terminals while the rounded nodes represent terminals. Upon reaching a non-terminal node, one must construct a term using that non-terminal

2.2.1 Operational Semantics for Logic Expressions

In order to get a feel for what an operational semantics is and how it is de ned, we will now examine the operational semantics for a very simple language: propositional boolean logic with no variables. The syntax of this language is as follows. An expression e is recursively de ned to consist of the values True and False, and the expressions e And

True j False

values The following is an equivalent syntax diagram: v pl.cs.jhu.edu

Red(x) Shiny(x)

Apple(x) indicates that if a thing is red and shiny, then that thing is an apple. This is, of course, not true; many red, shiny things exist which are not apples. Nonetheless, it is a valid logical statement. In our work, we will be de ning logical rules pertaining to a programming language; as a result, we have control over the space in which the

True And False ) False

This rule indicates that the boolean language code True And False evaluates to False. The absence of any preconditions above the line means that no conditions must be met; this operational semantics rule is always true. Rules with nothing above the line are termed axioms since they have no preconditions and so the conclusion always holds. As a rule

(Value Rule) v ) v

The value rule above is an axiom declaring that any value always evaluates to itself. This satis es our requirement and allows us to make use of the And rule. Using this formal logic approach, we can now prove that True And (False And True) ) False as follows: pl.cs.jhu.edu

False ) False True ) True True ) True False And True ) False True And (False And True) ) False

One may read the above proof tree as an explanation as to why True And (False And True) evaluates to False. We can choose to read that proof as follows: \\True And (False And True) evaluates to False by the And rule because we know True evaluates to True, that False And True evaluates to False, and that the logical and of true and false is false. We

2.2.2 Abstract Syntax

Our operational semantics rules have expressed the evaluation relation in terms of con-crete syntax using metavariables. Operators, such as the in x operator And, have ap-peared in textual format. This is a good representation for humans to read because it appeals to our intuition; it is not, however, an ideal computational representation. We read

(True And False) Implies ((Not True) And False)

Abstract: Implies( And(True,False) , And(Not(True),False) ) True False Implies And And Not False pl.cs.jhu.edu

true

There is a simple and direct relationship between the concrete syntax of a language and the abstract syntax. As mentioned above, the abstract syntax is a form which more directly represents the operations being performed whereas the concrete syntax is the form in which the operations are actually expressed. Part of the process of compiling or inter

J e2K )

For example, this relation indicates the following: J (True And False) Implies ((Not True) And False) = Implies( K True And False, (Not True) And False ) pl.cs.jhu.edu

True Or True And False

Abstract: And(Or(True,True),False) And Or False True True pl.cs.jhu.edu

True Or (True And False)

Abstract: Or(True,And(True,False)) Or True And True False True ) True False ) False pl.cs.jhu.edu

The algorithm must have as its input a

• nite number of arguments. The algorithm must consist of a nite number of steps. If the algorithm is given arguments for which the function is de ned, it must produce the correct answer within a nite amount of time. If the algorithm is given arguments for which the function is not de ned, it must either produce a clear error or otherwise not termi

j Function x e

v j (e) lower-case letters capital letters lower-case letters digits other characters variable values boolean values integer values function values value expressions parenthesized expressions j e And e j e Or e j Not e boolean expressions pl.cs.jhu.edu

j Let x = e In e

application expression conditional expressions let expression pl.cs.jhu.edu

j Let Rec f x = e In e recursive let expression

Note that in accordance with the above BNF, we will be using metavariables e, v, and x to represent expressions, values, and variables respectively. Note the last point: the metavariable x refers to an arbitrary F[ variable, not necessarily to the F[ variable x. Associativity in F[ works in a fashion very similar to OCaml. Function application, for

2.3.2 Variable Substitution

The main feature of F[ is higher-order functions, which also introduces variables. Recall that programs are computed by rewriting them: pl.cs.jhu.edu

Bound and Free Occurrences of Variables

Our compiled code mallocs but never frees. We will eventually run out of memory. A garbage collector is needed. De nition: In a run-time image, memory location n is garbage if it never will be read or written to again. There are many notions of garbage detection. The most common is to be somewhat more conservative and take garbage to be memory loca

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PDF	The Formal Semantics of Programming Languages: An Introduction All rights reserved. No part ofthis book may be reproduced in any form by any electronic or mechanical means (including photocopying recording

PDF	Object-Oriented Programming in C++ Fourth Edition Every effort has been made to make this book as complete and as accurate as languages have built-in data types. For instance a data type int

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