Empirical evaluation of reliability improvement in an evolving software product line

Krishnan, Sandeep; Lutz, Robyn R.; Goševa-Popstojanova, Katerina

doi:10.1145/1985441.1985458

Cited by 11 publications

(24 citation statements)

References 22 publications

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“…In previous work [16], we studied the failure and change trends at the component level for the commonalities and variations in the Eclipse product line. We found that as the product line evolves, fewer serious failures occur in components implementing commonalities than in components implementing variations, and that the common components also exhibit less change than the variable components over time.…”

Section: Eclipse Product Linementioning

confidence: 99%

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Are change metrics good predictors for an evolving software product line?

Krishnan

Strasburg

Lutz

et al. 2011

Proceedings of the 7th International Conference on Predictive Models in Software Engineering

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Background: Previous research on three years of early data for an Eclipse product identified some predictors of failureprone files that work well for that data set. Additionally, Eclipse has been used to explore characteristics of product line software in previous research. Aims: To assess whether change metrics are good predictors of failure-prone files over time for the family of products in the evolving Eclipse product line. Method: We repeat, to the extent possible, the decision tree portion of the prior study to assess our ability to replicate the method, and then extend it by including four more recent years of data. We compare the most prominent predictors with the previous study's results. We then look at the data for three additional Eclipse products as they evolved over time. We explore whether the set of good predictors change over time for one product and whether the set differs among products. Results: We find that change metrics are consistently good and incrementally better predictors across the evolving products in Eclipse. There is also some consistency regarding which change metrics are the best predictors. Conclusion: Change metrics are good predictors for failureprone files for the Eclipse product line. A small subset of these change metrics is fairly stable and consistent across products and releases.

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Section: Eclipse Product Linementioning

confidence: 99%

“…This is similar to the evolution and maintenance of a single system, except that it may happen to each system in the product line. In previous work we have shown that even files implementing commonalities experience change on an on-going basis [16].…”

Section: Introductionmentioning

confidence: 99%

Are change metrics good predictors for an evolving software product line?

Krishnan

Strasburg

Lutz

et al. 2011

Proceedings of the 7th International Conference on Predictive Models in Software Engineering

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“…Results show that variation components used only in individual products have the highest fault density, and are the most change prone. As in [10], common components reused in all four products had similar fault densities to the high-reuse variation components, but higher average code churn.…”

Section: Introductionmentioning

confidence: 64%

“…The only other work on this topic seems to be our previous study [10], which was based on analysis of post-release failures of an opensource SPL. Unlike [10], in this paper we study pre-release faults and change proneness of an industrial SPL. Results show that variation components used only in individual products have the highest fault density, and are the most change prone.…”

Section: Introductionmentioning

confidence: 99%

An Empirical Study of Pre-release Software Faults in an Industrial Product Line

Devine

Goseva-Popstajanova

Krishnan

et al. 2012

2012 IEEE Fifth International Conference on Software Testing, Verification and Validation

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Abstract-There is a lack of published studies providing empirical support for the assumption at the heart of product line development, namely, that through structured reuse later products will be less fault-prone. This paper presents results from an empirical study of pre-release fault and change proneness from four products in an industrial software product line. The objectives of the study are (1) to determine the association between various software metrics, as well as their correlation with the number of faults at the component level; (2) to characterize the fault and change proneness at various degrees of reuse; and (3) to determine how existing products in the software product line affect the quality of subsequently developed products and our ability to make predictions. The research results confirm, in a software product line setting, the findings of others that faults are more highly correlated to change metrics than to static code metrics. Further, the results show that variation components unique to individual products have the highest fault density and are the most prone to change. The longitudinal aspect of our research indicates that new products in this software product line benefit from the development and testing of previous products. For this case study, the number of faults in variation components of new products is predicted accurately using a linear model built on data from the previous products.

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“…Extensive experiments have been conducted in [152] and the results present that evolution of libre software is not SOC. Krishnan et al analyzed the failure trend and the change trend of common/variable components in software product line, and investigated the relationship between fail-ure and change [158]. Eclipse system, regarded as the evolving product line, was selected for experiment.…”

Section: To Empirically Validate Novel Ideas and Techniquesmentioning

confidence: 99%