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Publication search results
found 229 matches
- 2023
- Sousuke Amasaki:
On Effectiveness of Further Pre-training on BERT Models for Story Point Estimation. PROMISE 2023: 49-53 - Pragya Bhandari, Gema Rodríguez-Pérez:
BuggIn: Automatic Intrinsic Bugs Classification Model using NLP and ML. PROMISE 2023: 2-11 - Sivajeet Chand, Sushant Kumar Pandey, Jennifer Horkoff, Miroslaw Staron, Miroslaw Ochodek, Darko Durisic:
Comparing Word-Based and AST-Based Models for Design Pattern Recognition. PROMISE 2023: 44-48 - Umutcan Karakas, Ayse Tosun:
Automated Fairness Testing with Representative Sampling. PROMISE 2023: 54-63 - Foutse Khomh:
Harnessing Predictive Modeling and Software Analytics in the Age of LLM-Powered Software Development (Invited Talk). PROMISE 2023: 1 - Tim Menzies:
Model Review: A PROMISEing Opportunity. PROMISE 2023: 64-68 - David Reid, Kristiina Rahkema, James Walden:
Large Scale Study of Orphan Vulnerabilities in the Software Supply Chain. PROMISE 2023: 22-32 - Norbert Tihanyi, Tamás Bisztray, Ridhi Jain, Mohamed Amine Ferrag, Lucas C. Cordeiro, Vasileios Mavroeidis:
The FormAI Dataset: Generative AI in Software Security through the Lens of Formal Verification. PROMISE 2023: 33-43 - Ayberk Yasa, Ege Ergül, Hakan Erdogmus, Eray Tüzün:
Do Developers Fix Continuous Integration Smells? PROMISE 2023: 12-21 - Shane McIntosh, Eunjong Choi, Steffen Herbold:
Proceedings of the 19th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2023, San Francisco, CA, USA, 8 December 2023. ACM 2023 [contents] - 2022
- Bram Adams:
Release engineering in the AI world: how can analytics help? (keynote). PROMISE 2022: 1 - Hammad Ahmad, Colton Holoday, Ian Bertram, Kevin Angstadt, Zohreh Sharafi, Westley Weimer:
LOGI: an empirical model of heat-induced disk drive data loss and its implications for data recovery. PROMISE 2022: 52-61 - Khaled Walid Al-Sabbagh, Miroslaw Staron, Regina Hebig:
Predicting build outcomes in continuous integration using textual analysis of source code commits. PROMISE 2022: 42-51 - Peter Bludau, Alexander Pretschner:
Feature sets in just-in-time defect prediction: an empirical evaluation. PROMISE 2022: 22-31 - Tugce Coskun, Rusen Halepmollasi, Khadija Hanifi, Ramin Fadaei Fouladi, Pinar Çomak De Cnudde, Ayse Tosun:
Profiling developers to predict vulnerable code changes. PROMISE 2022: 32-41 - Fahad Al Debeyan, Tracy Hall, David Bowes:
Improving the performance of code vulnerability prediction using abstract syntax tree information. PROMISE 2022: 2-11 - Jediael Mendoza, Jason Mycroft, Lyam Milbury, Nafiseh Kahani, Jason Jaskolka:
On the effectiveness of data balancing techniques in the context of ML-based test case prioritization. PROMISE 2022: 72-81 - Mazen Mohamad, Jan-Philipp Steghöfer, Alexander Åström, Riccardo Scandariato:
Identifying security-related requirements in regulatory documents based on cross-project classification. PROMISE 2022: 82-91 - Dhasarathy Parthasarathy, Cecilia Ekelin, Anjali Karri, Jiapeng Sun, Panagiotis Moraitis:
Measuring design compliance using neural language models: an automotive case study. PROMISE 2022: 12-21 - Prantik Parashar Sarmah, Sridhar Chimalakonda:
API + code = better code summary? insights from an exploratory study. PROMISE 2022: 92-101 - Burak Yetistiren, Isik Ozsoy, Eray Tuzun:
Assessing the quality of GitHub copilot's code generation. PROMISE 2022: 62-71 - Shane McIntosh, Weiyi Shang, Gema Rodríguez-Pérez:
Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2022, Singapore, Singapore, 17 November 2022. ACM 2022, ISBN 978-1-4503-9860-2 [contents] - 2021
- Ibtissam Abnane, Ali Idri, Mohamed Hosni, Alain Abran:
Heterogeneous ensemble imputation for software development effort estimation. PROMISE 2021: 1-10 - Khaled Walid Al-Sabbagh, Miroslaw Staron, Regina Hebig, Francisco Gomes:
A classification of code changes and test types dependencies for improving machine learning based test selection. PROMISE 2021: 40-49 - Guru Prasad Bhandari, Amara Naseer, Leon Moonen:
CVEfixes: automated collection of vulnerabilities and their fixes from open-source software. PROMISE 2021: 30-39 - Leandro L. Minku:
Multi-stream online transfer learning for software effort estimation: is it necessary? PROMISE 2021: 11-20 - Leonardo Villalobos-Arias, Christian Quesada-López:
Comparative study of random search hyper-parameter tuning for software effort estimation. PROMISE 2021: 21-29 - Shane McIntosh, Xin Xia, Sousuke Amasaki:
PROMISE '21: 17th International Conference on Predictive Models and Data Analytics in Software Engineering, Athens Greece, August 19-20, 2021. ACM 2021, ISBN 978-1-4503-8680-7 [contents] - 2020
- Wisam Haitham Abbood Al-Zubaidi, Patanamon Thongtanunam, Hoa Khanh Dam, Chakkrit Tantithamthavorn, Aditya Ghose:
Workload-aware reviewer recommendation using a multi-objective search-based approach. PROMISE 2020: 21-30 - Hamoud Aljamaan, Amal Alazba:
Software defect prediction using tree-based ensembles. PROMISE 2020: 1-10
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