Combinatorial Sequence Testing Using Behavioral Programming and Generalized Coverage Criteria

Achiya Elyasaf; Eitan Farchi; Oded Margalit; Gera Weiss; Yeshayahu Weiss

Combinatorial Sequence Testing Using Behavioral Programming and Generalized Coverage Criteria

Achiya Elyasaf, Eitan Farchi, Oded Margalit, Gera Weiss, Yeshayahu Weiss

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Abstract

This paper tackles three main issues regarding test design: (1) it proposes a new way to model what to test; (2) it offers a framework for specifying coverage criteria that generalizes previous types of coverage; (3) it outlines a Bayesian approach to an informed exploitation-exploration balance in the context of testing. In addition to the theoretical contribution, we present an empirical evaluation with a proof-of-concept tool that we have developed to support the conceptual advantages and to illustrate practical benefits.

Original language	English
State	Published - 3 Jan 2022

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cs.SE

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2201.00522v1

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title = "Combinatorial Sequence Testing Using Behavioral Programming and Generalized Coverage Criteria",

abstract = " This paper tackles three main issues regarding test design: (1) it proposes a new way to model what to test; (2) it offers a framework for specifying coverage criteria that generalizes previous types of coverage; (3) it outlines a Bayesian approach to an informed exploitation-exploration balance in the context of testing. In addition to the theoretical contribution, we present an empirical evaluation with a proof-of-concept tool that we have developed to support the conceptual advantages and to illustrate practical benefits. ",

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AU - Farchi, Eitan

AU - Margalit, Oded

AU - Weiss, Gera

AU - Weiss, Yeshayahu

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PY - 2022/1/3

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N2 - This paper tackles three main issues regarding test design: (1) it proposes a new way to model what to test; (2) it offers a framework for specifying coverage criteria that generalizes previous types of coverage; (3) it outlines a Bayesian approach to an informed exploitation-exploration balance in the context of testing. In addition to the theoretical contribution, we present an empirical evaluation with a proof-of-concept tool that we have developed to support the conceptual advantages and to illustrate practical benefits.

AB - This paper tackles three main issues regarding test design: (1) it proposes a new way to model what to test; (2) it offers a framework for specifying coverage criteria that generalizes previous types of coverage; (3) it outlines a Bayesian approach to an informed exploitation-exploration balance in the context of testing. In addition to the theoretical contribution, we present an empirical evaluation with a proof-of-concept tool that we have developed to support the conceptual advantages and to illustrate practical benefits.

KW - cs.SE

M3 - Preprint

BT - Combinatorial Sequence Testing Using Behavioral Programming and Generalized Coverage Criteria

ER -

Combinatorial Sequence Testing Using Behavioral Programming and Generalized Coverage Criteria

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