COMIT II(ID:178/com008)String-handling and pattern-matching languageString-handling and pattern-matching language Places Structures: Related languages
References: in [ACM] CACM 6(03) (Mar 1963) view details The author admits that, while the reference manual is explicit on syntax, it must rely on detailed flow charts for specification of semantics. One wonders whether the specification of the compiler written in a high-level language would not be a better form of documentation than detailed flow charts. Interestingly, the manual itself is preserved;on Flexowriter tapes. Perhaps subsequent revisions could be updated automatically by an editing program? A good suggestion made by the author is that primers should be subjected to several iterations with feedback from users. He closes with the thought that manuals should be as accurate as the checked-out program, which would seem to argue for the point of view put forth above. in ACM Computing Reviews 5(01) January-February 1964 view details in Sass, M. and W. Wilkinson, eds. Computer Augmentation of Human Reasoning Spartan Books, Washington, D.C., 1965 view details in Sass, M. and W. Wilkinson, eds. Computer Augmentation of Human Reasoning Spartan Books, Washington, D.C., 1965 view details in Sass, M. and W. Wilkinson, eds. Computer Augmentation of Human Reasoning Spartan Books, Washington, D.C., 1965 view details [ Book ] FOSTER, J. M. List processing. American Elsevier Publ., New York, 1967, 54 pp. $4.50. This tiny (54 pages) monograph on list processing is a beautiful introduction to techniques which have been used for some time in many applications. Among the topics included are: 1) the representations of lists (both in the computer and externally); and 2) operations on lists, garbage collection, and typical list languages. One short chapter is also devoted to an example of list processing used in a program to perform syntactic analysis of language. All the examples in the book are programmed in an extended A~Go~ with added list processing functions, and are carefully chosen to illustrate important points about list processing. The book's principal weakness is its lack of depth, which is not really to be expected in such a brief monograph. The summary of the list processing languages IPL-V, LISP, FLIP, FLPL, and COMIT are too brief to give any real feeling for these languages to people who have not seen them before. But these are minor quibbles with a very fine book which will broaden the outlook of people who think of computers only as tools to manipulate numbers, and will allow them to begin to appreciate what can be done with list processing techniques for symbol manipula tion. D. a. Bobrow, Cambridge, Mass. in ACM Computing Reviews 9(01) January 1968 view details In general, string processing systems deal with data which is in the form of unstructured strings of characters. COMIT (Yngve, 1962), SNOBOL-3 (Farber, Griswold and Polansky, 1966) and SNOBOL4 (Griswold, Poage and Polansky, 1968) are three well-known string processing languages. Typical of the types of operation possible in these languages are matching, insertion, replacement and concatenation of strings and substrings. With the increasing usage of computers in many different fields, the distinction between numeric and non-numeric applications is becoming less apparent, as for example in information retrieval problems. Consequently it seems desirable that a single programming system should incorporate efficient numeric and non-numeric capabilities. The SP/1 system described here has been designed and implemented as a string processing system embedded in FORTRAN-IV. To avoid adding to the diversity of programming systems already in existence and since SNOBOL is a wellknown language whose syntax is readily adaptable to a FORTRAN environment, the operations provided in SP/I are similar to those available in SNOBOL-3. Unlike, for example DASH (Milner, 1967), which is a string processing extension embedded in ALGOL, SP/1 is both a syntactic and semantic extension to FORTRAN. The string processing statements can be represented by a set of macros which are expanded into FORTRAN statements by a macro generator (Macleod and Pengelly, 1969) prior to compilation. The macros have been designed so that there is a close similarity between the syntax of the corresponding SP/1 and SNOBOL3 statements. For example, the SNOBOL-3 statement REPEAT E "(" *V* ")" = V /S (REPEAT) deletes all the pairs of left and right parentheses from a string E. The corresponding SP/I statement is In addition, SP/1 provides a data type known as an association which may have a range of alternative values associated with it. This data type is in some ways similar to the pattern type in SNOBOL-IV and the assertion type in AXLE (Cohen and Wegstein, 1965). A further distinctive feature of SP/1 is that strings are stored as sequences of atoms where an atom is the smallest meaningful unit of the string. The size of an atom is determined on input as shown below, but normally an atom may be regarded as a single character symbol or as a group of consecutive alphameric characters. The latter could be the case for example in text processing where one atom would be equivalent to a word of text. This approach allows the processor to operate on strings composed of text words while retaining the capability to manipulate strings of individual symbols where required. This provides faster operation with a considerable saving in storage requirements in the text processing types of applications where the smallest logical unit of information is a word of text. Thus, essentially, there are two modes of operation, character and text, corresponding to the two types of storage. In the current version of SP/1 mixed mode operations are not allowable. The method of string storage, which involves a hash table, is described elsewhere (Macleod, 1969a). Extract: Introduction In general, string processing systems deal with data which is in the form of unstructured strings of characters. COMIT (Yngve, 1962), SNOBOL-3 (Farber, Griswold and Polansky, 1966) and SNOBOL4 (Griswold, Poage and Polansky, 1968) are three well-known string processing languages. Typical of the types of operation possible in these languages are matching, insertion, replacement and concatenation of strings and substrings. With the increasing usage of computers in many different fields, the distinction between numeric and non-numeric applications is becoming less apparent, as for example in information retrieval problems. Consequently it seems desirable that a single programming system should incorporate efficient numeric and non-numeric capabilities. The SP/1 system described here has been designed and implemented as a string processing system embedded in FORTRAN-IV. To avoid adding to the diversity of programming systems already in existence and since SNOBOL is a wellknown language whose syntax is readily adaptable to a FORTRAN environment, the operations provided in SP/I are similar to those available in SNOBOL-3. Unlike, for example DASH (Milner, 1967), which is a string processing extension embedded in ALGOL, SP/1 is both a syntactic and semantic extension to FORTRAN. The string processing statements can be represented by a set of macros which are expanded into FORTRAN statements by a macro generator (Macleod and Pengelly, 1969) prior to compilation. The macros have been designed so that there is a close similarity between the syntax of the corresponding SP/1 and SNOBOL3 statements. For example, the SNOBOL-3 statement REPEAT E "(" *V* ")" = V /S (REPEAT) deletes all the pairs of left and right parentheses from a string E. The corresponding SP/I statement is In addition, SP/1 provides a data type known as an association which may have a range of alternative values associated with it. This data type is in some ways similar to the pattern type in SNOBOL-IV and the assertion type in AXLE (Cohen and Wegstein, 1965). A further distinctive feature of SP/1 is that strings are stored as sequences of atoms where an atom is the smallest meaningful unit of the string. The size of an atom is determined on input as shown below, but normally an atom may be regarded as a single character symbol or as a group of consecutive alphameric characters. The latter could be the case for example in text processing where one atom would be equivalent to a word of text. This approach allows the processor to operate on strings composed of text words while retaining the capability to manipulate strings of individual symbols where required. This provides faster operation with a considerable saving in storage requirements in the text processing types of applications where the smallest logical unit of information is a word of text. Thus, essentially, there are two modes of operation, character and text, corresponding to the two types of storage. In the current version of SP/1 mixed mode operations are not allowable. The method of string storage, which involves a hash table, is described elsewhere (Macleod, 1969a). in The Computer Journal 13(3) view details in ACM Computing Reviews 15(04) April 1974 view details in SIGPLAN Notices 13(11) Nov 1978 view details in SIGPLAN Notices 13(11) Nov 1978 view details |