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From operational to declarative specifications using a genetic algorithm

Molina, Facundo et al · RI ITBA · 2019

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"In specification-based test generation, sometimes having a formal specification is not sufficient, since the specification may be in a different formalism from that required by the generation approach being used. In this paper, we deal with this problem specifically in the context in which, while having a formal specification in the form of an operational invariant written in a sequential programming language, one needs, for test generation, a declarative invariant in a logical formalism. We propose a genetic algorithm that given a catalog of common properties of invariants, such as acyclicity, sortedness and balance, attempts to evolve a conjunction of these that most accurately approximates an original operational specification. We present some details of the algorithm, and an experimental evaluation based on a benchmark of data structures, for which we evolve declarative logical invariants from operational ones."

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APA 7

Molina, F. E. A. (2019). From operational to declarative specifications using a genetic algorithm. RI ITBA. http://ri.itba.edu.ar/handle/20.500.14769/1627

MLA

Molina, Facundo et al. From operational to declarative specifications using a genetic algorithm. RI ITBA, 2019. http://ri.itba.edu.ar/handle/20.500.14769/1627.

Chicago

Molina, Facundo et al. 2019. From operational to declarative specifications using a genetic algorithm. RI ITBA. http://ri.itba.edu.ar/handle/20.500.14769/1627.

Harvard

Molina, F. E. A. 2019, From operational to declarative specifications using a genetic algorithm, RI ITBA, available at: http://ri.itba.edu.ar/handle/20.500.14769/1627 [Accessed 6 Aug. 2026].

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Title
From operational to declarative specifications using a genetic algorithm
Author / contributors
Molina, Facundo et al
Publisher
RI ITBA
Publication year
2019
ISSN
0270-5257
ISSN
0270-5257
Language
English

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