Semantics Of Programming Languages Pdf Freel: What You Need to Know

Description:The aim of the course is to introduce the structural, operational approach to programming language semantics. The course shows how this formalism is used to specify the meaning of some simple programming language constructs and to reason formally about semantic properties of programs.

Semantics Of Programming Languages Pdf Freel

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This book is an introduction to the mathematical theory of programming languages. It is in tended to provide a first course, one that is suitable for all university students of Computer Science to take early in their education.

The book con tains much basic mathematical material on data, syntax and semantics. There are some seemingly advanced features and contemporary topics that may not be common in the elementary textbook literature: data types and their algebraic theory, real numbers, interface definition languages, algebraic models of abstract syntax, use of algebraic operational seman tics, connections with computability theory, virtual machines and compiler correctness.

An excellent introduction to a wide range of programming language concepts. They are all uniformly and carefully explained, using techniques that are very useful in practice for both analysis and implementation of programming languages.

The Formal Semantics of Programming Languages provides the basic mathematical techniques necessary for those who are beginning a study of the semantics and logics of programming languages. These techniques will allow students to invent, formalize, and justify rules with which to reason about a variety of programming languages. Although the treatment is elementary, several of the topics covered are drawn from recent research, including the vital area of concurency. The book contains many exercises ranging from simple to miniprojects.Starting with basic set theory, structural operational semantics is introduced as a way to define the meaning of programming languages along with associated proof techniques. Denotational and axiomatic semantics are illustrated on a simple language of while-programs, and fall proofs are given of the equivalence of the operational and denotational semantics and soundness and relative completeness of the axiomatic semantics. A proof of Godel's incompleteness theorem, which emphasizes the impossibility of achieving a fully complete axiomatic semantics, is included. It is supported by an appendix providing an introduction to the theory of computability based on while-programs. Following a presentation of domain theory, the semantics and methods of proof for several functional languages are treated. The simplest language is that of recursion equations with both call-by-value and call-by-name evaluation. This work is extended to lan guages with higher and recursive types, including a treatment of the eager and lazy lambda-calculi. Throughout, the relationship between denotational and operational semantics is stressed, and the proofs of the correspondence between the operation and denotational semantics are provided. The treatment of recursive types - one of the more advanced parts of the book - relies on the use of information systems to represent domains. The book concludes with a chapter on parallel programming languages, accompanied by a discussion of methods for specifying and verifying nondeterministic and parallel programs.

A programming language is a system of notation for writing computer programs.[1] Most programming languages are text-based formal languages, but they may also be graphical. They are a kind of computer language.

The description of a programming language is usually split into the two components of syntax (form) and semantics (meaning), which are usually defined by a formal language. Some languages are defined by a specification document (for example, the C programming language is specified by an ISO Standard) while other languages (such as Perl) have a dominant implementation that is treated as a reference. Some languages have both, with the basic language defined by a standard and extensions taken from the dominant implementation being common.

The term computer language is sometimes used interchangeably with programming language.[2] However, the usage of both terms varies among authors, including the exact scope of each. One usage describes programming languages as a subset of computer languages.[3] Similarly, languages used in computing that have a different goal than expressing computer programs are generically designated computer languages. For instance, markup languages are sometimes referred to as computer languages to emphasize that they are not meant to be used for programming.[4]One way of classifying computer languages is by the computations they are capable of expressing, as described by the theory of computation. The majority of practical programming languages are Turing complete,[5] and all Turing complete languages can implement the same set of algorithms. ANSI/ISO SQL-92 and Charity are examples of languages that are not Turing complete, yet are often called programming languages.[6][7] However, some authors restrict the term "programming language" to Turing complete languages.[1][8]

Another usage regards programming languages as theoretical constructs for programming abstract machines and computer languages as the subset thereof that runs on physical computers, which have finite hardware resources.[9] John C. Reynolds emphasizes that formal specification languages are just as much programming languages as are the languages intended for execution. He also argues that textual and even graphical input formats that affect the behavior of a computer are programming languages, despite the fact they are commonly not Turing-complete, and remarks that ignorance of programming language concepts is the reason for many flaws in input formats.[10]

In most practical contexts, a programming language involves a computer; consequently, programming languages are usually defined and studied this way.[11] Programming languages differ from natural languages in that natural languages are only used for interaction between people, while programming languages also allow humans to communicate instructions to machines.

The domain of the language is also worth consideration. Markup languages like XML, HTML, or troff, which define structured data, are not usually considered programming languages.[12][13][14] Programming languages may, however, share the syntax with markup languages if a computational semantics is defined. XSLT, for example, is a Turing complete language entirely using XML syntax.[15][16][17] Moreover, LaTeX, which is mostly used for structuring documents, also contains a Turing complete subset.[18][19]

Programming languages usually contain abstractions for defining and manipulating data structures or controlling the flow of execution. The practical necessity that a programming language support adequate abstractions is expressed by the abstraction principle.[20] This principle is sometimes formulated as a recommendation to the programmer to make proper use of such abstractions.[21]

Slightly later, programs could be written in machine language, where the programmer writes each instruction in a numeric form the hardware can execute directly. For example, the instruction to add the value in two memory locations might consist of 3 numbers: an "opcode" that selects the "add" operation, and two memory locations. The programs, in decimal or binary form, were read in from punched cards, paper tape, magnetic tape or toggled in on switches on the front panel of the computer. Machine languages were later termed first-generation programming languages (1GL).

The next step was the development of the so-called second-generation programming languages (2GL) or assembly languages, which were still closely tied to the instruction set architecture of the specific computer. These served to make the program much more human-readable and relieved the programmer of tedious and error-prone address calculations.

The first high-level programming languages, or third-generation programming languages (3GL), were written in the 1950s. An early high-level programming language to be designed for a computer was Plankalkül, developed for the German Z3 by Konrad Zuse between 1943 and 1945. However, it was not implemented until 1998 and 2000.[22]

The increased use of high-level languages introduced a requirement for low-level programming languages or system programming languages. These languages, to varying degrees, provide facilities between assembly languages and high-level languages. They can be used to perform tasks that require direct access to hardware facilities but still provide higher-level control structures and error-checking.

The 1960s and 1970s also saw considerable debate over the merits of structured programming, and whether programming languages should be designed to support it.[35] Edsger Dijkstra, in a famous 1968 letter published in the Communications of the ACM, argued that Goto statements should be eliminated from all "higher level" programming languages.[36]

The 1980s were years of relative consolidation. C++ combined object-oriented and systems programming. The United States government standardized Ada, a systems programming language derived from Pascal and intended for use by defense contractors. In Japan and elsewhere, vast sums were spent investigating the so-called "fifth-generation" languages that incorporated logic programming constructs.[37] The functional languages community moved to standardize ML and Lisp. Rather than inventing new paradigms, all of these movements elaborated upon the ideas invented in the previous decades.

The rapid growth of the Internet in the mid-1990s created opportunities for new languages. Perl, originally a Unix scripting tool first released in 1987, became common in dynamic websites. Java came to be used for server-side programming, and bytecode virtual machines became popular again in commercial settings with their promise of "Write once, run anywhere" (UCSD Pascal had been popular for a time in the early 1980s). These developments were not fundamentally novel; rather, they were refinements of many existing languages and paradigms (although their syntax was often based on the C family of programming languages). 2ff7e9595c