Prioritizing Test Gaps by Risk in Industrial Practice: An Automated Approach and Multimethod Study

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Context.</i> Untested code changes, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">test gaps</i>, pose a significant risk for software projects. Since test gaps increase the probability of defects, managing test gaps and their individual risk is important, especially for rapidly changing software systems. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective.</i> This study aims at gaining an understanding of test gaps in industrial practice establishing criteria for precise prioritization of test gaps by their risk, informing practitioners that need to manage, review, and act on larger sets of test gaps. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Method.</i> We propose an automated approach for prioritizing test gaps based on key risk criteria. By means of an analysis of 31 historical test gap reviews from 8 industrial software systems of our industrial partners Munich Re and LV 1871, and by conducting semi-structured interviews with the 6 quality engineers that authored the historical test gap reviews, we validate the transferability of the identified risk criteria, such as code criticality and complexity metrics. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results.</i> Our automated approach exhibits a ranking performance equivalent to expert assessments, in that test gaps labelled as risky in historical test gap reviews are prioritized correctly, on average, on the 30th percentile. In some scenarios, our automated ranking system even outpaces expert assessments, especially for test gaps in central code—for non-developers an opaque code property. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusion.</i> This research underscores the industrial need of test gap risk estimation techniques to assist test management and quality assurance teams in identifying and addressing critical test gaps. Our multimethod study shows that even a lightweight prioritization approach helps practitioners to identify high-risk test gaps efficiently and to filter out low-risk test gaps.

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Journal
IEEE Transactions on Software Engineering
Published
2025-03-29
DOI
https://doi.org/10.1109/tse.2025.3556248
Primary Topic
Safety Systems Engineering in Autonomy
Type
article
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article

Prioritizing Test Gaps by Risk in Industrial Practice: An Automated Approach and Multimethod Study

Roman Haas, Sven Apel, Michael Sailer, Mitchell Joblin et al.
IEEE Transactions on Software Engineering
Safety Systems Engineering in Autonomy
article

Prioritizing Test Gaps by Risk in Industrial Practice: An Automated Approach and Multimethod Study

Roman Haas, Sven Apel, Michael Sailer, Mitchell Joblin, Elmar Juergens
article en

Abstract

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Context.</i> Untested code changes, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">test gaps</i>, pose a significant risk for software projects. Since test gaps increase the probability of defects, managing test gaps and their individual risk is important, especially for rapidly changing software systems. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective.</i> This study aims at gaining an understanding of test gaps in industrial practice establishing criteria for precise prioritization of test gaps by their risk, informing practitioners that need to manage, review, and act on larger sets of test gaps. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Method.</i> We propose an automated approach for prioritizing test gaps based on key risk criteria. By means of an analysis of 31 historical test gap reviews from 8 industrial software systems of our industrial partners Munich Re and LV 1871, and by conducting semi-structured interviews with the 6 quality engineers that authored the historical test gap reviews, we validate the transferability of the identified risk criteria, such as code criticality and complexity metrics. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results.</i> Our automated approach exhibits a ranking performance equivalent to expert assessments, in that test gaps labelled as risky in historical test gap reviews are prioritized correctly, on average, on the 30th percentile. In some scenarios, our automated ranking system even outpaces expert assessments, especially for test gaps in central code—for non-developers an opaque code property. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusion.</i> This research underscores the industrial need of test gap risk estimation techniques to assist test management and quality assurance teams in identifying and addressing critical test gaps. Our multimethod study shows that even a lightweight prioritization approach helps practitioners to identify high-risk test gaps efficiently and to filter out low-risk test gaps.

IEEE Transactions on Software EngineeringVol. 51(5)
Saarland University (DE)
Openalex Percentile: Top 93%
Safety Systems Engineering in Autonomy
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