PROMISE 2022 – Proceedings

18th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2022)

Frontmatter

Keynote

Release Engineering in the AI World: How Can Analytics Help? (Keynote)
Bram Adams
(Queen’s University, Canada)

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Papers

Improving the Performance of Code Vulnerability Prediction using Abstract Syntax Tree Information
Fahad Al Debeyan, Tracy Hall, and David Bowes
(Lancaster University, UK)

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Measuring Design Compliance using Neural Language Models: An Automotive Case Study
Dhasarathy Parthasarathy, Cecilia Ekelin, Anjali Karri, Jiapeng Sun, and Panagiotis Moraitis
(Volvo, Sweden; Chalmers University of Technology, Sweden)

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Feature Sets in Just-in-Time Defect Prediction: An Empirical Evaluation
Peter Bludau and Alexander Pretschner
(fortiss, Germany; TU Munich, Germany)

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Profiling Developers to Predict Vulnerable Code Changes
Tugce Coskun, Rusen Halepmollasi, Khadija Hanifi, Ramin Fadaei Fouladi, Pinar Comak De Cnudde, and Ayse Tosun
(Istanbul Technical University, Turkey; Ericsson Security Research, Turkey)

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Predicting Build Outcomes in Continuous Integration using Textual Analysis of Source Code Commits
Khaled Al-Sabbagh, Miroslaw Staron, and Regina Hebig
(Chalmers University of Technology, Sweden; University of Gothenburg, Sweden)

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LOGI: An Empirical Model of Heat-Induced Disk Drive Data Loss and Its Implications for Data Recovery
Hammad Ahmad, Colton Holoday, Ian Bertram, Kevin Angstadt, Zohreh Sharafi, and Westley Weimer
(University of Michigan, USA; MathWorks, USA; St. Lawrence University, USA; Polytechnique Montréal, Canada)

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Assessing the Quality of GitHub Copilot’s Code Generation
Burak Yetistiren, Isik Ozsoy, and Eray Tuzun
(Bilkent University, Turkey)

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On the Effectiveness of Data Balancing Techniques in the Context of ML-Based Test Case Prioritization
Jediael Mendoza, Jason Mycroft, Lyam Milbury, Nafiseh Kahani, and Jason Jaskolka
(Carleton University, Canada)

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Identifying Security-Related Requirements in Regulatory Documents Based on Cross-Project Classification
Mazen Mohamad, Jan-Philipp Steghöfer, Alexander Åström, and Riccardo Scandariato
(Chalmers University of Technology, Sweden; University of Gothenburg, Sweden; Xitaso, Germany; Comentor, Sweden; Hamburg University of Technology, Germany)

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API + Code = Better Code Summary? Insights from an Exploratory Study
Prantik Parashar Sarmah and Sridhar Chimalakonda
(IIT Tirupati, India)

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