Formal Languages and Compilation (2nd Edition) (Texts in Computer Science)

Formal Languages and Compilation (2nd Edition) (Texts in Computer Science)

Stefano Crespi Reghizzi, Luca Breveglieri, Angelo Morzenti

Language: English

Pages: 408

ISBN: 1447168682

Format: PDF / Kindle (mobi) / ePub

This fully revised and expanded new edition elucidates the elegance and simplicity of the fundamental theory underlying Formal Languages and Compilation.

Retaining the reader-friendly, minimalist style of the first edition, this uniquely versatile textbook describes the essential principles and methods used for defining the syntax of artificial languages, and for designing efficient parsing algorithms and syntax-directed translators with semantic attributes. A comprehensive selection of topics is presented within a rigorous, unified framework, illustrated by numerous practical examples.

Features and topics:
* Presents a novel conceptual approach to parsing algorithms that applies to extended BNF grammars, together with a parallel parsing algorithm (NEW)
* Supplies supplementary teaching tools, including course slides and exercises with solutions, at an associated website
* Unifies the concepts and notations used in different approaches, enabling an extended coverage of methods with a reduced number of definitions
* Systematically discusses ambiguous forms, allowing readers to avoid pitfalls when designing grammars
* Describes all algorithms in pseudocode, so that detailed knowledge of a specific programming language is not necessary
* Makes extensive usage of theoretical models of automata, transducers and formal grammars
* Includes concise coverage of algorithms for processing regular expressions and finite automata
* Introduces static program analysis based on flow equations

This clearly-written, classroom-tested textbook is an ideal guide to the fundamentals of this field for advanced undergraduate and graduate students in computer science and computer engineering. Some background in programming is required, and readers should also be familiar with basic set theory, algebra and logic.

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Software engineering method for designing well-structured translators by taking advantage of the syntactic modularity of grammar rules. We are going to clarify the distinction between the syntax and semantics of a language. The etymology of the two terms says rather vaguely that the former has to do with the structure and the latter with the meaning or the message to be communicated. In linguistics the two terms have often been taken as emblems representing forms and contents, respectively, but.

Example 5.34 (Breaking a text into lines (Reps)) A text has to be segmented into lines. The syntax generates a series of words separated by a space (written ⊥). The text has to be displayed in a window having a width of W≥1 characters and an unbounded height, in such a way that each line contains a maximum number of left-aligned words and no word is split across lines. By hypothesis no word has length greater than W. Assume the columns are numbered from 1 to W. The grammar computes the.

Candidate is a pair 〈q B ,a〉 in Q×(Σ∪{⊣}). The intended meaning is that token a is a legal look-ahead for the current activation of machine M B in state q B . When parsing begins, the initial state of the axiomatic machine M S is encoded by candidate 〈0 S ,⊣〉, which says that the end-of-text character is expected when the entire input is reduced to the axiom S. To calculate the candidates for a given grammar or machine net, we use a function traditionally named closure. Definition 4.26.

There is a convergence conflict, because the look-ahead set is the same, i.e., {e}. Fig. 4.16Grammar with net and pilot (Example 4.36); the double-line arcs in the pilot are convergent; the pilot has a convergence conflict The pilot in Fig. 4.16 does not have any shift–reduce conflicts and is trivially free from reduce–reduce conflicts, but having a convergence conflict, it violates the ELR(1) condition. Similarly Fig. 4.19 shows a grammar, its machine net representation and the corresponding.

Uses a vector stack and is generated by the grammar in Fig. 4.8 with the ELR(1) pilot in Fig. 4.13 In every vsms on the stack, the second field of each candidate is the elemid index, which points back to some inner position of the stack. Index elemid is equal to the current stack position for all the candidates in the closure part of a stack element, and it points to some previous position for the candidates of the base. The reduction handles are highlighted by means of solid backward pointers,.

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