Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/14816
Title: How Good Are My Tests?
Authors: Bowes, D
Hall, T
Petric, J
Shippey, T
Turhan, B
Keywords: Unit testing;Test quality;Metrics
Issue Date: 2017
Publisher: ACM
Citation: Proceedings of the 8th Workshop on Emerging Trends in Software Metrics (WETSOM 17), Buenos Aires, Argentina, pp. 9-14, 20 - 28 May, (2017)
Abstract: Background: Test quality is a prerequisite for achieving production system quality. While the concept of quality is multidimensional, most of the effort in testing context has been channelled towards measuring test effectiveness. Objective: While effectiveness of tests is certainly important, we aim to identify a core list of testing principles that also address other quality facets of testing, and to discuss how they can be quantified as indicators of test quality. Method: We have conducted a two-day workshop with our industry partners to come up with a list of relevant principles and best practices expected to result in high quality tests. We then utilised our academic and industrial training materials together with recommendations in practitioner oriented testing books to refine the list. We surveyed existing literature for potential metrics to quantify identified principles. Results: We have identified a list of 15 testing principles to capture the essence of testing goals and best practices from quality perspective. Eight principles do not map to existing test smells and we propose metrics for six of those. Further, we have identified additional potential metrics for the seven principles that partially map to test smells. Conclusion: We provide a core list of testing principles along with a discussion of possible ways to quantify them for assessing goodness of tests. We believe that our work would be useful for practitioners in assessing the quality of their tests from multiple perspectives including but not limited to maintainability, comprehension and simplicity.
URI: http://bura.brunel.ac.uk/handle/2438/14816
ISBN: 978-1-5386-2807-2
Appears in Collections:Dept of Computer Science Research Papers

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