Programming with abstract data types
Open accessAbstract
The motivation behind the work in very-high-level languages is to ease the programming task by providing the programmer with a language containing primitives or abstractions suitable to his problem area. The programmer is then able to spend his effort in the right place; he concentrates on solving his problem, and the resulting program will be more reliable as a result. Clearly, this is a worthwhile goal. Unfortunately, it is very difficult for a designer to select in advance all the abstractions which the users of his language might need. If a language is to be used at all, it is likely to be used to solve problems which its designer did not envision, and for which the abstractions embedded in the language are not sufficient. This paper presents an approach which allows the set of built-in abstractions to be augmented when the need for a new data abstraction is discovered. This approach to the handling of abstraction is an outgrowth of work on designing a language for structured programming. Relevant aspects of this language are described, and examples of the use and definitions of abstractions are given.
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References 4 · Cited by 397
Research works printed but not linked: 10
- Parnas, D.L. Information distribution aspects of design methodology, Proceedings of the IFIP Congress, August 1971.
- DiJkstra, E. W. Notes on structured programming. Structured Pro~rammln~, A.P.I.C. Studies in Data Processing, No. 8, Academic Press, New York, 1972, pp 1-81.
- Schuman, S. A. and P. Jorrand. Definition mechanisms in extensible programming languages. Proceedln~s of the AFIPS, Vol. 37, 1970, pp 9-19.
- Mealy, G. Another look at data. Proceedings of the AFIPS, Vol. 31, 1967, pp 525-534.
- Balzer, R. M. Dataless programming. ProceedinKs of the AFIPS, Vol. 31, 1967, pp 557-566.
- Earley, J. Toward an understanding of data struc- tures. Comm. of the ACM, Vol. 14, No. I0 (October 1971), pp 617-627.
- Daley, R. C., and P. G. Neumann. A general- purpose file system for secondary storage. Proceedings of the AFIPS, Vol. 27, 1965~ pp 213-229.
- Morris, J. H., Jr. Protection in progranmling languages. Comm. of the ACM, Vol. 16, N__oo. i (January 1973), pp 15-21.
- Zilles, S. N. Procedural encapsulation: a linguistic protection technique. SIGPLANNotices, Vol. 8, N__o. 9 (September 1973), pp 140-146.
- Liskov, B. H. A design methodology for reliable software systems. Proceedings of the AFIPS, Vol. 41, 1972~ pp 191-199.
- Authors
- Liskov, B., & Zilles, S.
- Affiliations
- Massachusetts Institute of Technology (US)
- IBM (United States) (US)
- Venue
- ACM SIGPLAN Notices
- Published
- 1974-03-28
- Volume
- 9
- Issue
- 4
- Pages
- 50-59
- ISSN
- 0362-1340 (ISSN-L)
- 1558-1160
- OpenAlex
- W3160136729
- Cited by
- 397
- References
- 4
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 5 · 2023: 5 · 2022: 7 · 2021: 7 · 2020: 5 · 2019: 6 · 2018: 3 · 2017: 3 · 2016: 4 · 2015: 1 · 2014: 4 · 2013: 5 · 2012: 4
- FWCI
- 33.72
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM SIGPLAN Notices (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, programming, and type systems
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Software Engineering Methodologies
- Keywords
- abstract data types, data abstraction, language design, structured programming, very high level languages, programming language design
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