Improving the Effectiveness of Traceability Link Recovery using Hierarchical Bayesian NetworksTechnical
Traceability is a fundamental component of the modern software development process that helps to ensure properly functioning, secure programs. However, traceability tasks incur high costs in terms of effort and time and are often prone to errors. This has prompted a wealth of research on automated approaches that draw relationships between pairs of textual software artifacts using similarity measures. Despite the progress made toward practical automation, such approaches currently have two major drawbacks that inhibit their effectiveness. Namely, current techniques typically only utilize a single measure of artifact similarity, and cannot simultaneously model (implicit and explicit) relationships across groups of diverse structured and unstructured development artifacts.
In this paper, we illustrate how these limitations can be overcome through the use of a tailored probabilistic model. To this end, we design and implement a HierarchiCal PrObabilistic Model for SoftwarE Traceability (Comet) that is able to predict candidate trace links. Comet is capable of modeling relationships between artifacts by combining the complimentary observational prowess of multiple measures of textual similarity. Additionally, our model can holistically incorporate information from a diverse set of sources, including developer expertise and transitive (often implicit) relationships among groups of software artifacts, to improve prediction accuracy. We conduct a comprehensive empirical evaluation of Comet that illustrates our approach is consistently more effective across datasets than existing baseline techniques, and outperforms past approaches on average when considering multiple information sources. Additionally, we worked with a major telecommunication company to develop a Continuous Integration (CI) plugin implementing Comet. A survey with industry developers who used the Comet plugin illustrates its potential for practical applicability.
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15:00 - 16:00: A9-TraceabilityPaper Presentations / New Ideas and Emerging Results / Demonstrations / Technical Papers / Software Engineering in Practice at Silla Chair(s): Andrea ZismanThe Open University | |||
15:00 - 15:12 Talk | A Novel Approach to Tracing Safety Requirements and State-Based Design ModelsTechnical Technical Papers | ||
15:12 - 15:24 Talk | Establishing Multilevel Test-to-Code Traceability Links Technical Papers Robert WhiteUniversity College London, UK, Jens KrinkeUniversity College London, Raymond TanUniversity College London | ||
15:24 - 15:30 Talk | Synthesis of Assurance Cases for Software CertificationNIER New Ideas and Emerging Results Hamid BagheriUniversity of Nebraska-Lincoln, USA, Eunsuk KangCarnegie Mellon University, Niloofar MansoorUniversity of Nebraska - Lincoln Pre-print | ||
15:30 - 15:33 Talk | TimeTracer: A Tool for Back in Time Traceability ReplayingDemo Demonstrations Christoph Mayr-DornJohannes Kepler University Linz, Michael VierhauserJohannes Kepler University Linz, Felix KeplingerJohannes Kepler University, Linz, Stefan BichlerJohannes Kepler University, Linz, Alexander EgyedJohannes Kepler University, Linz | ||
15:33 - 15:45 Talk | Lack of Adoption of Units of Measurement Libraries: Survey and AnecdotesSEIP Software Engineering in Practice Steve McKeeverDepartment of Informatics and Media, Uppsala University, Sweden, Omar-Alfred SalahDepartment of Informatics and Media, Uppsala University, Sweden | ||
15:45 - 15:57 Talk | Improving the Effectiveness of Traceability Link Recovery using Hierarchical Bayesian NetworksTechnical Technical Papers Kevin MoranWilliam & Mary/George Mason University, David Nader PalacioWilliam & Mary, Carlos Bernal-CárdenasWilliam and Mary, Denys PoshyvanykWilliam and Mary, Daniel McCrystalWilliam & Mary, Chris ShenefielCisco Systems, Jeff JohnsonCisco Systems Pre-print Media Attached |