Powered by
18th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2022), November 17, 2022,
Singapore, Singapore
18th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2022)
Frontmatter
Keynote
Papers
Improving the Performance of Code Vulnerability Prediction using Abstract Syntax Tree Information
Fahad Al Debeyan,
Tracy Hall, and
David Bowes
(Lancaster University, UK)
@InProceedings{PROMISE22p11,
author = {Fahad Al Debeyan and Tracy Hall and David Bowes},
title = {Improving the Performance of Code Vulnerability Prediction using Abstract Syntax Tree Information},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {11-10},
doi = {10.1145/3558489.3559066},
year = {2022},
}
Publisher's Version
Published Artifact
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)
@InProceedings{PROMISE22p21,
author = {Dhasarathy Parthasarathy and Cecilia Ekelin and Anjali Karri and Jiapeng Sun and Panagiotis Moraitis},
title = {Measuring Design Compliance using Neural Language Models: An Automotive Case Study},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {21-20},
doi = {10.1145/3558489.3559067},
year = {2022},
}
Publisher's Version
Feature Sets in Just-in-Time Defect Prediction: An Empirical Evaluation
Peter Bludau and
Alexander Pretschner
(fortiss, Germany; TU Munich, Germany)
@InProceedings{PROMISE22p31,
author = {Peter Bludau and Alexander Pretschner},
title = {Feature Sets in Just-in-Time Defect Prediction: An Empirical Evaluation},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {31-30},
doi = {10.1145/3558489.3559068},
year = {2022},
}
Publisher's Version
Published Artifact
Artifacts Available
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)
@InProceedings{PROMISE22p41,
author = {Tugce Coskun and Rusen Halepmollasi and Khadija Hanifi and Ramin Fadaei Fouladi and Pinar Comak De Cnudde and Ayse Tosun},
title = {Profiling Developers to Predict Vulnerable Code Changes},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {41-40},
doi = {10.1145/3558489.3559069},
year = {2022},
}
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)
@InProceedings{PROMISE22p51,
author = {Khaled Al-Sabbagh and Miroslaw Staron and Regina Hebig},
title = {Predicting Build Outcomes in Continuous Integration using Textual Analysis of Source Code Commits},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {51-50},
doi = {10.1145/3558489.3559070},
year = {2022},
}
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)
@InProceedings{PROMISE22p61,
author = {Hammad Ahmad and Colton Holoday and Ian Bertram and Kevin Angstadt and Zohreh Sharafi and Westley Weimer},
title = {LOGI: An Empirical Model of Heat-Induced Disk Drive Data Loss and Its Implications for Data Recovery},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {61-60},
doi = {10.1145/3558489.3559071},
year = {2022},
}
Publisher's Version
Assessing the Quality of GitHub Copilot’s Code Generation
Burak Yetistiren,
Isik Ozsoy, and
Eray Tuzun
(Bilkent University, Turkey)
@InProceedings{PROMISE22p71,
author = {Burak Yetistiren and Isik Ozsoy and Eray Tuzun},
title = {Assessing the Quality of GitHub Copilot’s Code Generation},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {71-70},
doi = {10.1145/3558489.3559072},
year = {2022},
}
Publisher's Version
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)
@InProceedings{PROMISE22p81,
author = {Jediael Mendoza and Jason Mycroft and Lyam Milbury and Nafiseh Kahani and Jason Jaskolka},
title = {On the Effectiveness of Data Balancing Techniques in the Context of ML-Based Test Case Prioritization},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {81-80},
doi = {10.1145/3558489.3559073},
year = {2022},
}
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)
@InProceedings{PROMISE22p91,
author = {Mazen Mohamad and Jan-Philipp Steghöfer and Alexander Åström and Riccardo Scandariato},
title = {Identifying Security-Related Requirements in Regulatory Documents Based on Cross-Project Classification},
booktitle = {Proc.\ PROMISE},
publisher = {ACM},
pages = {91-90},
doi = {10.1145/3558489.3559074},
year = {2022},
}
Publisher's Version
proc time: 0.62