Abstract Data Types and Software Validation.

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Bibliographic Details
Title: Abstract Data Types and Software Validation.
Authors: Guttag, John V.1, Horowitz, Ellis1, Musser, David R.1, Horning, J. J.
Source: Communications of the ACM. Dec1978, Vol. 21 Issue 12, p1048-1064. 17p. 9 Diagrams.
Subjects: Abstract data types (Computer science), Computer programming, Software validation, Programming languages, Axioms, Computer science
Abstract: A data abstraction can be naturally specified using algebraic axioms. The virtue of these axioms is that they permit a representation-independent formal specification of a data type. An example is given which shows how to employ algebraic axioms at successive levels of implementation. The major thrust of the paper is twofold. First, it is shown how the use of algebraic axiomatizations can simplify the process of proving the correctness of an implementation of an abstract data type. Second, semi-automatic tools are described which can be used both to automate such proofs of correctness and to derive an immediate implementation from the axioms. This implementation allows for limited testing of programs at design time, before a conventional implementation is accomplished. [ABSTRACT FROM AUTHOR]
Copyright of Communications of the ACM is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="AR" term="%22Guttag%2C+John+V%2E%22">Guttag, John V.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Horowitz%2C+Ellis%22">Horowitz, Ellis</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Musser%2C+David+R%2E%22">Musser, David R.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Horning%2C+J%2E+J%2E%22">Horning, J. J.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Communications+of+the+ACM%22">Communications of the ACM</searchLink>. Dec1978, Vol. 21 Issue 12, p1048-1064. 17p. 9 Diagrams.
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  Data: A data abstraction can be naturally specified using algebraic axioms. The virtue of these axioms is that they permit a representation-independent formal specification of a data type. An example is given which shows how to employ algebraic axioms at successive levels of implementation. The major thrust of the paper is twofold. First, it is shown how the use of algebraic axiomatizations can simplify the process of proving the correctness of an implementation of an abstract data type. Second, semi-automatic tools are described which can be used both to automate such proofs of correctness and to derive an immediate implementation from the axioms. This implementation allows for limited testing of programs at design time, before a conventional implementation is accomplished. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Communications of the ACM is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1145/359657.359666
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      – Code: eng
        Text: English
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        PageCount: 17
        StartPage: 1048
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      – SubjectFull: Abstract data types (Computer science)
        Type: general
      – SubjectFull: Computer programming
        Type: general
      – SubjectFull: Software validation
        Type: general
      – SubjectFull: Programming languages
        Type: general
      – SubjectFull: Axioms
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      – SubjectFull: Computer science
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            – D: 01
              M: 12
              Text: Dec1978
              Type: published
              Y: 1978
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