Results and Experiences from an Empirical Study of Fault Reports in Industrial Projects

Børretzen, Jon Arvid; Conradi, Reidar

doi:10.1007/11767718_33

Cited by 9 publications

(11 citation statements)

References 6 publications

(5 reference statements)

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“…They analyzed different categories of faults and their contribution to the total number of faults in the system. Børretzen and Conradi [4] performed a study of four business-critical systems to investigate their fault profiles. They classified the faults into multiple categories and analyzed the distribution of different types of faults.…”

Section: Related Workmentioning

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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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: Related Workmentioning

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

View full text Add to dashboard Cite

show abstract

“…They analyzed different categories of faults and their contribution to the total number of faults in the system. Børretzen and Conradi [7] performed a study of four business-critical systems to investigate their fault profiles. They classified the faults into multiple categories and analyzed the distribution of different types of faults.…”

Section: Related Workmentioning

confidence: 99%

Empirical evaluation of reliability improvement in an evolving software product line

Krishnan

Lutz

Goševa-Popstojanova

2011

Proceedings of the 8th Working Conference on Mining Software Repositories

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Reliability is important to software product-line developers since many product lines require reliable operation. It is typically assumed that as a software product line matures, its reliability improves. Since post-deployment failures impact reliability, we study this claim on an open-source software product line, Eclipse. We investigate the failure trend of common components (reused across all products), highreuse variation components (reused in five or six products) and low-reuse variation components (reused in one or two products) as Eclipse evolves. We also study how much the common and variation components change over time both in terms of addition of new files and modification of existing files. Quantitative results from mining and analysis of the Eclipse bug and release repositories show that as the product line evolves, fewer serious failures occur in components implementing commonality, and that these components also exhibit less change over time. These results were roughly as expected. However, contrary to expectation, components implementing variations, even when reused in five or more products, continue to evolve fairly rapidly. Perhaps as a result, the number of severe failures in variation components shows no uniform pattern of decrease over time. The paper describes and discusses this and related results.

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“…Although most quantitative results of the studies are already published [4,12,18], we felt that there is a need for summarizing the experience in using problem reports, identifying common questions and concerns, and raising the level of discussion by answering them. Examples from similar research are provided to further illustrate the points.…”

Section: Introductionmentioning

confidence: 99%

Revisiting the problem of using problem reports for quality assessment

Mohagheghi

Conradi

Børretzen

2006

Proceedings of the 2006 International Workshop on Software Quality

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In this paper, we describe our experience with using problem reports from industry for quality assessment. The non-uniform terminology used in problem reports and validity concerns have been subject of earlier research but are far from settled. To distinguish between terms such as defects or errors, we propose to answer three questions on the scope of a study related to what (problem appearance or its cause), where (problems related to software; executable or not; or system), and when (problems recorded in all development life cycles or some of them). Challenges in defining research questions and metrics, collecting and analyzing data, generalizing the results and reporting them are discussed. Ambiguity in defining problem report fields and missing, inconsistent or wrong data threatens the value of collected evidence. Some of these concerns could be settled by answering some basic questions related to the problem reporting fields and improving data collection routines and tools.

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Results and Experiences from an Empirical Study of Fault Reports in Industrial Projects

Cited by 9 publications

References 6 publications

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

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

Empirical evaluation of reliability improvement in an evolving software product line

Revisiting the problem of using problem reports for quality assessment

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