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 – Preliminary Table of Contents

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

Papers

Improving the Performance of Code Vulnerability Prediction using Abstract Syntax Tree Information
Fahad Al Debeyan ORCID logo, Tracy Hall ORCID logo, and David Bowes ORCID logo
(Lancaster University, UK)
Article Search Artifacts Available
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 ORCID logo and Alexander Pretschner ORCID logo
(fortiss, Germany; TU Munich, Germany)
Article Search Artifacts Available
Profiling Developers to Predict Vulnerable Code Changes
Tugce Coskun ORCID logo, Rusen Halepmollasi ORCID logo, Khadija Hanifi ORCID logo, Ramin Fadaei Fouladi ORCID logo, Pinar Comak De Cnudde ORCID logo, and Ayse Tosun ORCID logo
(Istanbul Technical University, Turkey; Ericsson Security Research, n.n.)
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Predicting Build Outcomes in Continuous Integration using Textual Analysis of Source Code Commits
Khaled Al-Sabbagh ORCID logo, Miroslaw Staron ORCID logo, and Regina Hebig ORCID logo
(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 AhmadORCID logo, Colton Holoday, Ian Bertram, Kevin Angstadt, Zohreh Sharafi, and Westley Weimer ORCID logo
(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 YetistirenORCID logo, Isik OzsoyORCID logo, and Eray TuzunORCID logo
(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 ORCID logo, Nafiseh Kahani ORCID logo, and Jason Jaskolka ORCID logo
(Carleton University, Canada)
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Identifying Security-Related Requirements in Regulatory Documents Based on Cross-Project Classification
Mazen Mohamad ORCID logo, Jan-Philipp Steghöfer, Alexander Åström, and Riccardo Scandariato ORCID logo
(Chalmers University of Technology, Sweden; University of Gothenburg, Sweden; Volvo GTT, n.n.; Hamburg University of Technology, Germany)
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API + Code = Better Code Summary? Insights from an Exploratory Study
Prantik Parashar Sarmah ORCID logo and Sridhar Chimalakonda ORCID logo
(IIT Tirupati, India)
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