S
Sebastian Elbaum
Researcher at University of Virginia
Publications - 209
Citations - 9610
Sebastian Elbaum is an academic researcher from University of Virginia. The author has contributed to research in topics: Test suite & Regression testing. The author has an hindex of 44, co-authored 199 publications receiving 8704 citations. Previous affiliations of Sebastian Elbaum include Lincoln University (Pennsylvania) & University of Idaho.
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Journal ArticleDOI
Supporting Controlled Experimentation with Testing Techniques: An Infrastructure and its Potential Impact
TL;DR: The infrastructure that is being designed and constructed to support controlled experimentation with testing and regression testing techniques is described and the impact that this infrastructure has had and can be expected to have.
Journal ArticleDOI
Test case prioritization: a family of empirical studies
TL;DR: In this article, the authors empirically compared the effectiveness of fine granularity and coarse granularity prioritization techniques using both controlled experiments and case studies, and found that the incorporation of measures of fault proneness into prioritization technique improves their effectiveness.
Proceedings ArticleDOI
Prioritizing test cases for regression testing
TL;DR: Can prioritization techniques be effective when aimed at specific modified versions; what tradeoffs exist between fine granularity and coarse granularity prioritized techniques; and can the incorporation of measures of fault proneness into prioritization technique improve their effectiveness?
Proceedings ArticleDOI
Incorporating varying test costs and fault severities into test case prioritization
TL;DR: This study presents a new metric for assessing the rate of fault detection of prioritized test cases that incorporates varying test case and fault costs and presents the results of a case study illustrating the application of the metric.
Proceedings ArticleDOI
Techniques for improving regression testing in continuous integration development environments
TL;DR: This work presents algorithms that make continuous integration processes more cost-effective, involving algorithms that are relatively inexpensive and do not rely on code coverage information -- two requirements for conducting testing cost- effective in this context.