“Meaning” may be assigned to a string in a context-free language by defining “attributes” of the symbols in a derivation tree for that string. The attributes can be defined by functions associated with each production in the grammar. This paper examines the implications of this process when some of the attributes are “synthesized”, i.e., defined solely in terms of attributes of thedescendants of the corresponding nonterminal symbol, while other attributes are “inherited”, i.e., defined in terms of attributes of theancestors of the nonterminal symbol. An algorithm is given which detects when such semantic rules could possibly lead to circular definition of some attributes. An example is given of a simple programming language defined with both inherited and synthesized attributes, and the method of definition is compared to other techniques for formal specification of semantics which have appeared in the literature.

/pdf/semantics-of-context-free-languages-a86zhto24u.pdf

Semantics of context-free languages

A parsing algorithm which seems to be the most efficient general context-free algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar top-down algorithm. It has a time bound proportional to n3 (where n is the length of the string being parsed) in general; it has an n2 bound for unambiguous grammars; and it runs in linear time on a large class of grammars, which seems to include most practical context-free programming language grammars. In an empirical comparison it appears to be superior to the top-down and bottom-up algorithms studied by Griffiths and Petrick.

An efficient context-free parsing algorithm

This paper presents an approach to writing specifications for parts of software systems. The main goal is to provide specifications sufficiently precise and complete that other pieces of software can be written to interact with the piece specified without additional information. The secondary goal is to include in the specification no more information than necessary to meet the first goal. The technique is illustrated by means of a variety of examples from a tutorial system.

/pdf/a-technique-for-software-module-specification-with-examples-481hl6c15s.pdf

A technique for software module specification with examples

Quantitative fuzzy semantics

This report contains recommendations on academic programs in computer science which were developed by the ACM Curriculum Committee on Computer Science. A classification of the subject areas contained in computer science is presented and twenty-two courses in these areas are described. Prerequisites, catolog descriptions, detailed outlines, and annotated bibliographies for these courses are included. Specific recommendations which have evolved from the Committee's 1965 Preliminary Recommendations are given for undergraduate programs. Graduate programs in computer science are discussed, and some recommendations are presented for the development of master's degree programs. Ways of developing guidelines for doctoral programs are discussed, but no specific recommendations are made. The importance of service courses, minors, and continuing education in computer science is emphasized. Attention is given to the organization, staff requirements, computer resources, and other facilities needed to implement computer science educational programs.

Curriculum 68: Recommendations for academic programs in computer science: a report of the ACM curriculum committee on computer science

In this section the algorithmic language EULER is described first informally and then formally by its syntax and semantics. An attempt has been made to generalize and extend some of the concepts of ALGOL, thus creating a language which is simpler and yet more flexible than ALGOL 60. A second objective in developing this language was to show that a useful programming language which can be processed with reasonable efficiency can be defined in rigorous formality.

EULER: a generalization of ALGOL, and its formal definition: Part II

A method for defining programming languages is developed which introduces a rigorous relationship between structure and meaning. The structure of a language is defined by a phrase structure syntax, the meaning in terms of the effects which the execution of a sequence of interpretation rules exerts upon a fixed set of variables, called the Environment. There exists a one-to-one correspondence between syntactic rules and interpretation rules, and the sequence of executed interpretation rules is determined by the sequence of corresponding syntactic reductions which constitute a parse. The individual interpretation rules are explained in terms of an elementary and obvious algorithmic notation. A constructive method for evaluating a text is provided, and for certain decidable classes of languages their unambiguity is proven. As an example, a generalization of ALGOL is described in full detail to demonstrate that concepts like block-structure, procedures, parameters etc. can be defined adequately and precisely by this method.

EULER: a generalization of ALGOL, and its formal definition

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EULER: a generalization of ALGOL, and its formal definition: Part II

EULER: a generalization of ALGOL, and its formal definition