Comparing the Effectiveness of Testing Techniques

Weyuker, Elaine J.

doi:10.1007/978-3-540-78917-8_9

Cited by 7 publications

(3 citation statements)

References 27 publications

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“…It produces, formally and exhaustively (under certain assumptions and thanks to the mathematical theory presented in the previous sections), all the feasible execution paths of the source code. It is thus stronger (in the sense of [26]) than any other structural (path, branch, du-path, etc.) coverage objective.…”

Section: Discussionmentioning

confidence: 95%

A Qualitative Reasoning Model for Software Testing, based on Combinatorial Geometry

Xanthakis¹,

Gioan

2021

Artificial Intelligence Methods for Software Engineering

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Let us first give a short summary of the paper. We introduce an operational qualitative model for numerical algorithms. This model enables qualitative algorithmic reasoning during the unit testing process, supported by an automatic generation of boundary test data. It contains the spatial encoding of all the functionally equivalent regions (called homodromies). The model, viewed as a qualitative abstraction of the algorithm, is automatically generated thanks to multiple targeted executions of its instrumented basic conditions, that permit the interpolation of a set of linear equations and their corresponding hyperplanes. All feasible paths (when all basic conditions are linear) are identified in the form a Ternary Decision Tree. Each feasible execution path corresponds to a geometric region supported and/or delimited by a finite set of hyperplanes of the vector space. Oriented Matroids allow the encoding of the relative positions of all such regions of various dimensions, in a purely combinatorial way, using a finite signed set system, supported by a rich mathematical theory. This model uses a qualitative space algebra and enables qualitative reasoning: regions are identified according to qualitatively valued inputs, which are, in their turn, propagated through them. The proposed model permits a global/local envisionment 331

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Section: Discussionmentioning

confidence: 95%

A Qualitative Reasoning Model for Software Testing, based on Combinatorial Geometry

Xanthakis¹,

Gioan

2021

Artificial Intelligence Methods for Software Engineering

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“…Weyuker et al [12,[26][27][28] has been working with comparison of testing techniques using different approaches. The work reported in [27] shows two ways to compare testing techniques: a formal and an empirical.…”

Section: Related Workmentioning

confidence: 99%

“…The work reported in [27] shows two ways to compare testing techniques: a formal and an empirical. Its main message is that people from industry think it is difficult to model systems and a large case study is more effective to compare testing techniques.…”

Section: Related Workmentioning

confidence: 99%

A Framework for GUI Testing Based on Use Case Design

Bertolini

Mota

2010

2010 Third International Conference on Software Testing, Verification, and Validation Workshops

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Today GUIs are not exclusive of desktops and web applications. They can be found in a widely variety of embedded systems such as cellular phones, TVs, cars, etc. GUI testing is an emergent approach to assure software quality. In this paper, we show how to evaluate some GUI testing techniques and the importance of controlled experiments in order to have statistical confidence. Furthermore, as GUI design changes often during the development process, test cases need to be updated as well. Therefore, we also propose a general framework to GUI test case design and generation based on model-based testing and GUI capturereplay tools. The framework is easily extended to support different test case generation algorithms and script languages. It also allows one to explore functional as well as non-functional requirements, such as usability, accessibility, reliability, and so on.

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