ESEC/FSE 2022 CoLos
30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022)
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18th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2022), November 17, 2022, Singapore, Singapore

PROMISE 2022 – Proceedings

Contents - Abstracts - Authors
Twitter: https://twitter.com/esecfse

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

Frontmatter

Title Page
Message from the Chairs

Keynote

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

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
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
Feature Sets in Just-in-Time Defect Prediction: An Empirical Evaluation
Peter Bludau and Alexander Pretschner
(fortiss, Germany; TU Munich, Germany)
Publisher's Version
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
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
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
Assessing the Quality of GitHub Copilot’s Code Generation
Burak Yetistiren, Isik Ozsoy, and Eray Tuzun
(Bilkent University, Turkey)
Publisher's Version Info
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
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
API + Code = Better Code Summary? Insights from an Exploratory Study
Prantik Parashar Sarmah and Sridhar Chimalakonda
(IIT Tirupati, India)
Publisher's Version

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