Download Programming Languages and Operational Semantics: A Concise by Maribel Fernández PDF
By Maribel Fernández
Delivering a concise creation to the fundamental thoughts in programming languages, utilizing ideas from operational semantics, this booklet highlights 3 significant programming paradigms:
• crucial languages: the most beneficial properties of those languages are illustrated with examples in Java, Python, C;
• sensible languages: glossy languages similar to ML and Haskell are used to explain the sensible variety of programming;
• common sense languages: the final a part of the e-book offers an outline of good judgment programming utilizing Prolog.
Following a basic description of every kin of languages, their semantics are studied utilizing summary machines and structural operational semantics. Programming Languages and Operational Semantics offers an in-depth research of the elemental strategies in programming languages rather than an insignificant survey of languages, aiding the certainty of the elemental notions in programming languages over easily describing their properties.
It is addressed to undergraduate scholars, as a supplement to programming classes.
Read or Download Programming Languages and Operational Semantics: A Concise Overview (Undergraduate Topics in Computer Science) PDF
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Extra resources for Programming Languages and Operational Semantics: A Concise Overview (Undergraduate Topics in Computer Science)
Sample text
However, instead of translating our property, we can adapt the induction principle to work directly on the data structures of interest (specifically, recursively-defined structures such as strings, lists or trees). Let us consider first the case of lists. Assume we denote an empty list by nil, and a non-empty list by cons(h, l) where h is the head element and l is the tail of the list. For simplicity, let us assume that we are building lists of natural numbers, so h is a natural number. For example, the list containing just the element 0 is written cons(0, nil).
Our universal set). An axiom is simply an element of T . The standard notation for axioms is: t A rule is a pair (H, c) where – H is a non-empty subset {h 1 , . . , h n } of T , called the hypotheses or premises of the rule; – c is an element of T , called the conclusion of the rule. The standard notation for rules is: h1 . . hn c Rules may have conditions, which we write on the side (we give examples below). 4 Induction 37 We now define precisely the inductive set specified by a collection of axioms and rules.
Tn ) under the assumption that the property holds for the trees t1 , . . , tn . In the induction step, P(t1 ), . . , P(tn ) are the induction hypotheses. Similarly, to define a function on all the elements of a set defined by structural induction, it is sufficient to define it for the basic elements, and to give a recursive definition for the elements defined by constructors. More precisely, to define function f on a set defined by structural induction from the basic elements l1 , . . , lm , using constructors c1 , .