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)

Publisher's Version Article: fsews22promisemain-key1-p doi:10.1145/3558489.3570199

Papers

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

Publisher's Version Published Artifact Artifacts Available Article: fsews22promisemain-p1-p doi:10.1145/3558489.3559066

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)

Publisher's Version Article: fsews22promisemain-p3-p doi:10.1145/3558489.3559067

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

Publisher's Version Published Artifact Artifacts Available Article: fsews22promisemain-p5-p doi:10.1145/3558489.3559068

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)

Publisher's Version Article: fsews22promisemain-p6-p doi:10.1145/3558489.3559069

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)

Publisher's Version Article: fsews22promisemain-p12-p doi:10.1145/3558489.3559070

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)

Publisher's Version Article: fsews22promisemain-p15-p doi:10.1145/3558489.3559071

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

Publisher's Version Article: fsews22promisemain-p16-p doi:10.1145/3558489.3559072

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)

Publisher's Version Article: fsews22promisemain-p18-p doi:10.1145/3558489.3559073

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)

Publisher's Version Article: fsews22promisemain-p20-p doi:10.1145/3558489.3559074

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

Publisher's Version Article: fsews22promisemain-p23-p doi:10.1145/3558489.3559075

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