Showing papers on "String (computer science) published in 1968"

Semantics of context-free languages

Abstract: “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.

An efficient context-free parsing algorithm

Abstract: 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.

Programming Techniques: Regular expression search algorithm

Abstract: A method for locating specific character strings embedded in character text is described and an implementation of this method in the form of a compiler is discussed. The compiler accepts a regular expression as source language and produces an IBM 7094 program as object language. The object program then accepts the text to be searched as input and produces a signal every time an embedded string in the text matches the given regular expression. Examples, problems, and solutions are also presented.

Regular Expression Search Algorithm

Abstract: A method for locating specific character strings embedded in character text is described and an implementation of this method in the form of a compiler is discussed. The compiler accepts a regular expression as source language and produces an IBM 7094 program as object language. The object program then accepts the text to be searched as input and produces a signal every time an embedded string in the text matches the given regular expression. Examples, problems, and solutions are also presented.

How Long is a Piece of String

Abstract: This is a summary of the problems which are involved in the apparently trivial task of measuring the length of a sinuous line on a map. It represents an extended review of the publication Cartometric Measurements, by H. Kishimoto. It is concerned with three basic problems: (1) the sorts of errors which may result from using different instruments and methods of measurement and how these may be corrected: (2) the sorts of errors which may occur in the map and how these may be corrected: 3) the fundamental problem of what is 'length'. Extensive use is made of East European literature on these subjects.

Repeated items and decay in memory

Abstract: Subjects were presented with a string of digits, following which they were required to judge which of two test digits occurred more recently in the list. As predicted by a trace-decay model, when the earlier of the test digits was repeated, performance was worse than in the control condition.

Languages of encoded line patterns

Abstract: By treating patterns as statements in a two-dimensional language, it is possible to apply linguistic theory to pattern analysis and recognition. In this paper, line patterns are encoded into string form using the chain code developed by Freeman. A class of patterns, or pattern language, encodes to a set of strings that is examined using theory that exists for string languages and automata. Pattern languages formed on the basis of equations in two variables and various pattern properties are related to the hierarchy of string language classes. The known relationships between classes of string languages and classes of automata can then be applied to determine bounds on the time and memory required to recognize the various patterns. Results can be extended to other forms of pattern encoding provided that a suitable translator can be constructed.

The theory of languages

Abstract: Let ~ be a finite set of symbols, or alphabet. Define ~* to be the set of all finite length strings of symbols in X, including ~, the string of length 0. A language is a subset of X*, for some alphabet ~. Clearly, the natural languages and programming languages are languages in the formal sense. The theory of languages is concerned with the description of languages, their recognition and processing. A language may contain an infinite number of strings, so at the least, one needs a finite description of the language. Particular types of finite descriptions will yield useful properties of the languages they define, especially when the class of languages they define is "small" (i.e., not every language of conceivable interest is described). If C is the class of languages defined by a certain type of description, one would like to know whether membership in C is preserved under various operations. One would like to know that the languages in class C could be recognized quickly and simply, especially if one were attempting to develop a compiling system for a language or languages in C. Also useful are characterizations of languages in C, so one can tell easily if a given language is in class C. Finally, one wants algorithms, if they exist, to answer certain questions about the languages in C, such as: "Is string w in language L?" In this article, we will give the principal methods of describing languages and the principal results concerning each method.

Method and apparatus for detecting and diagnosing computer error conditions

Abstract: Method and apparatus for detecting and diagnosing error conditions in any of a plurality of discrete units within a digital computer system effected by execution of test routines each of which is adapted to detect and diagnose errors in a selected one of the units Each test routine comprises a plurality of test strings which are serially executed Each test string includes one or more test cases and the strings are sequenced within the routine such that strings containing larger numbers of cases are executed prior to those having fewer numbers of cases Execution of each test case within a string is effected by setting the unit to be tested to a predetermined initial state, feeding a clock pulse to the unit, determining the resultant state of the unit, and comparing the resultant state with a predetermined expected state Failure of any such comparison indicates failure of a test case and the detection of an error Failure of all test cases within a single test string indicates that a particular diagnosable error condition associated with that string is the error source Failure of the first test case within a string is utilized to set a binary error element while the success of any subsequent test case within the string will reset the element In one embodiment, each test case is repeatedly executed a predetermined number of times in order to detect intermittent errors

Auxiliary turnoff circuit for a thyristor switch

Abstract: An auxiliary turnoff circuit for a thyristor switch string in which a normally open switch, connected across at least one of the thyristors in the string, is caused to repeatedly close should the string permanently latch on. The first closure is timed to occur after the automatic turnoff circuit has failed to open the switch string and the closed intervals are greater than the normal recovery time of the thyristors in the string.

A Semantic Analyzer for English Sentences

Abstract: A system for semantic analysis of a wide range of English sentence forms is described. The system has been implemented in LISP 1.5 on the System Development Corporation (SDC) time-shared computer. Semantic analysis is defined as the selection of a unique word sense for each word in a natural-language sentence string and its bracketing in an underlying deep structure of that string. The conclusion is drawn that a semantic analyzer differs from a syntactic analyzer primarily in requiring, in addition to syntactic word-classes, a large set of semantic word-classes. A second conclusion is that the use of semantic event forms eliminates the need for selection restrictions and projection rules as posited by Katz. A discussion is included of the relations of elements of this system to the elements of the Katz theory.

Property grammars and table machines

Abstract: The purpose of this paper is to generalize the methods of automata theory to accommodate infinite input alphabets and to propose a method of describing computer languages such as ALGOL-60 with more reliance on grammatical methods and less reliance on semantic constraints. Our chief concern is a natural generalization of a context-free grammar which we call a context-free property grammar. The generalization is straight-forward and can be used in similar fashion to define regular property grammars, context-sensitive property grammars, etc. The chief result is that these contextfree property grammars generate precisely the set of languages recognized by a non-determinated pushdown table machine, which is a straight forward generalization of a pushdown machine. Again it is clear that other kinds of automata have corresponding table versions. The language-machine correspondence is preserved in such a matter that efficient processing schemes for context-free property grammars are suggested by the well-known schemes for context free languages. Before beginning, we mention some mathematical conventions used. If A is a set, then A* represents the set of all finite sequences of elements from A. If w is in A*, then l(w) is the length of word w. The symbol ∈ represents the null or length zero word. A typical element of A* will be described by ai...an with the understanding that if n = 0, the null string ∈ is represented and there are no ai in the string. If n is a positive integer, then An represents the set of n dimensional vectors whose components are from A. A typical element of An is represented as (ai,..., an). If I is a set, then AI represents the set of all functions from I to A. Finally 2A represents the set of all subsets of A.

A Universal Syntax-Directed Top-Down Analyzer

Abstract: An algorithm is described that will recognize, and fully analyze, strings of unbounded length, using the rewriting rules of any context-free grammar. It uses a finite random access store, three pushdown tapes, and a counter. It imposes no restrictions on the grammar defined by the rewriting rules, excepting only that it be a context-free phrase structure grammar. The analysis printed out is a linearized form of the structural description tree (or trees, in an ambiguous case) of the input string. A proof that the analyzer will always stop in a finite time is provided. The upper bound on the running time increases exponentially with input string length.

Musical string instrument

Abstract: An elementary bowed string instrument having a string tensioned by an extendable spring anchored at one end to enable the string to be tuned visually by a marker cooperating with a pointer carried by the string.

FLEX - A Flexible Extendable Language

Abstract: : The FLEX system consists of merged 'hardware' and 'software' that is optimized towards handling algorithmic operations in an interactive, man-machine dialog. The basic form is that of a hardware implementation of a parametric compiler embedded in an environment that is well-suited for semantically describing and pragmatically executing a large class of languages. The semantic language is called FLEX, includes the compiler-compiler as a string operator and is used as the basic medium for carrying out processes. It is of a higher-level nature and may itself be used for describing many algorithmic processes. The machine itself is designed to be of the desk-top variety and sell at a low price.

Phoneme-to-grapheme translation of english

Abstract: One of the problems of connected speech recognition concerns the transcription of a sequence of phonemes (or any other lower level linguistic units) into a sequence of words of a sentence. Although this problem appears to be unsolvable in its full generality, several subproblems can be solved by imposing certain specific constraints. The paper describes possible solutions to some of these subproblems and presents some results obtained using a PDP-6 computer. Using a phoneme-to-word dictionary and the structure of the English language, a computer program transforms the phoneme string of a simple English sentence into a word string. The program uses a tree-structure mechanism to keep track of the possibilities at various stages. Since the dictionary has to be finite, the program asks for human assistance when it is unable to find a suitable match. If the input phoneme string is likely to have errors, the matching routine can be required to check for possible confusions among phonemes.

Satiation of a verbal cue in problem solving in French speaking children

Abstract: Forty French speaking fourth grade children were randomly assigned to groups and repeated either a relevant cue, the word “corde” (string), or an irrelevant cue, the word “porte” (door) for 1, 15, 30 or 60 repetitions prior to attempting to solve a measurement of circumference problem. The solution of the problem involved the use of a string. Latency to solution of the problem was statistically greater for the groups who continually repeated the relevant cue as compared to those who continually repeated the irrelevant cue.

String Handling in ALGOL

Abstract: DASH is designed to allow a user to handle strings and perform efficient arithmetic in the same language. There are a number of languages designed to handle strings (Farber, Griswold and Polonsky, 1964 and 1966; Guzman and Mclntyre 1966), but their arithmetic facilities are slight. On the other hand, on many computers the only "general purpose" languages at present implemented (e.g. ALGOL 60, FORTRAN) are almost purely arithmetic. This hampers both users and those whose job is computer science education. The procedures to be described aim to provide string processing of the SNOBOL type (Farber et al, 1966) to the extent that is reasonably possible within ALGOL. The description is informal, and some details are omitted for brevity. The reader will benefit from a knowledge of SNOBOL, though it is hoped an understanding can be gained without this knowledge. The superimposition of procedures of this type on ALGOL will be rendered easier and more natural with a facility such as the proposed record handling of Wirth and Hoare (1966).

CHAMP—character manipulation procedures

Abstract: A new programming language facility for symbol manipulation is described. String procedures may be declared and called in a standard ALGOL context. ALGOL procedures can in turn be called by string procedures so that numeric and symbolic processes may conveniently be programmed together. Concatenation and a variant of SNOBOL's pattern matching make up a set of primitive commands. These are assembled together into conditional expressions which are to be used to provide alternative computational patterns. Arrays of strings are processed using quantifiers. The class of things which may be assigned to an identifier can be restricted by a procedure expressed in the notation. The language facilities have been implemented in the ALGOL compiler for the Burroughs B5500.

The Structure of SNOBOL4

Abstract: The SNOBOL4 programming language was developed by Griswold, Poage and Polonski (1). It combines facilities available in problem oriented languages with string manipulation facilities, pattern matching facilities and facilities for compilation during execution. The present description attempts to accomplish three objectives. It is an introduction to SNOBOL4 for the programmer with previous programming experience in some programming language but not necessarily previous experience with SNOBOL3. It is intended also to provide dynamic insights into the mechanisms for statement execution, and to describe source language structures in terms of the information structures to which they give rise during execution. It is felt that dynaamic insights into the way in which source statements are executed help not only the system programmer but also the average user. This description is based on reference 1 and on two very worthwhile days of discussion with the authors of SNOBOL4 at Holmdel. The author is indebted also to John Kelly for fruitful discussion of aspects of SNOBOL4 and for proofreading the manuscript.

String descriptions of data for display

Abstract: A Picture Description Language (PDL) and a Picture Calculus have been developed for the formal description and manipulation of pictures. A display program which utilizes PDL string descriptions as the principal data structure has been developed. This display program permits the generation of drawings on a computer-controlled cathode ray tube and allows transformations according to the rules of the picture calculus. A description of the complete data structure for this display program is presented, and the type of transformations and manipulations possible are shown.