2024
Journal
- ZHENG, S., ADAMS, B. and HASSAN, A.E. (2024). On Build Hermeticity in Bazel-based Build Systems, IEEE Software, IEEE, to appear. BibTeX
- KAMATH, D.M., ADAMS, B. and HASSAN, A.E. (2024). Lightweight Dynamic Build Batching Algorithms for Continuous Integration, Empirical Software Engineering, Springer, to appear. BibTeX
- PATEL, H., BOUCHER, D., FALLAHZADEH, E., HASSAN, A.E. and ADAMS, B. (2024). A State-of-the-practice Release-readiness Checklist for Generative AI-based Software Products, IEEE Software, IEEE, to appear. BibTeX
- YASMIN, J., WANG, J., TIAN, Y., and ADAMS, B. (2024). An Empirical Study of Developers' Challenges in Implementing Workflows as Code: A Case Study on Apache Airflow, Journal of Software and Systems (JSS), Elsevier, to appear. BibTeX
- OREAMUNO, E.L., KHAN, R.F., BANGASH, A.A., STINSON, C. and ADAMS, B. (2024). The State of Documentation Practices of Third-party Machine Learning Models and Datasets, IEEE Software, 41(5), p.52-59, IEEE. BibTeX
- KAMATH, D.M., FERNANDES, E., ADAMS, B. and HASSAN, A.E. (2024). On Combining Commit Grouping and Build Skip Prediction to Reduce Redundant Continuous Integration Activity, Empirical Software Engineering, 29(6), Springer. BibTeX
- ZHENG, S., ADAMS, B. and HASSAN, A.E. (2024). Does Using Bazel Help Speed Up Continuous Integration Builds?, Empirical Software Engineering, 29(5), Springer. BibTeX
- OUATITI, Y.E., SAYAGH, M., KERZAZI, N., ADAMS, B. and HASSAN, A.E. (2024). The impact of Concept drift and Data leakage on Log Level Prediction Models, Empirical Software Engineering, 29(5), Springer. BibTeX
- PATEL, H., ADAMS, B. and HASSAN, A.E. (2024). Post Deployment Recycling of Machine Learning Models - Don't Throw Away Your Old Models!, Empirical Software Engineering, 29(4), Springer. BibTeX
- EBRAHIMI, A., ADAMS, B., OLIVA, G.A. and HASSAN, A.E. (2024). A Large-Scale Exploratory Study on the Proxy Pattern in Ethereum, Empirical Software Engineering, 29(4), Springer. BibTeX
- ZHAO, Z., CHEN, Y., BANGASH, A.A., ADAMS, B. and HASSAN, A.E. (2024). An Empirical Study of Challenges in Machine Learning Asset Management, Empirical Software Engineering, 29(4), Springer. BibTeX
- MALIK, A., ADAMS, B. and HASSAN, A.E. (2024). Towards Graph-Anonymization of Software Analytics Data: Empirical Study on JIT Defect Prediction, Empirical Software Engineering, 29(4), Springer. BibTeX
- NAYEBI, M. and ADAMS, B. (2024). Image-based Communication on Social Coding Platforms, Journal of Software: Evolution and Process (JSEP), 36(5), Wiley. BibTeX
- BAJAJ, R., FERNANDES, E., ADAMS, B. and HASSAN, A.E. (2024). Unreproducible builds: Time to fix, causes, and correlation with external ecosystem factors , Empirical Software Engineering, 29(1), Springer. BibTeX
Conference
- OLEWICKI, D., HABCHI, S. and ADAMS, B. (2024). An empirical study on code review activity prediction and its impact in practice, in Proceedings of the ACM on Software Engineering (PACMSE), Issue FSE 2024 (Porto de Galinhas, Brazil), to appear. (Acceptance ratio: 121/483=25.1%) BibTeX
- OLEWICKI, D., HABCHI, S., NAYROLLES, M., FARAMARZI, M., CHANDAR, S. and ADAMS, B. (2024). On the Costs and Benefits of Adopting Lifelong Learning for Software Analytics: Empirical Study on Brown Build and Risk Prediction, in Proceedings of the Software Engineering In Practice (SEIP) track at the 46th International Conference on Software Engineering, ICSE (Lisbon, Portugal), p. 275-286. (Acceptance ratio: 45/120=37.5%) BibTeX (Distinguished Paper Award)
- MACEDO, M., TIAN, Y., COGO, F. and ADAMS, B. (2024). Exploring the Impact of the Output Format on the Evaluation of Large Language Models for Code Translation, in Proceedings of the 2024 Special Event of AI Foundation Models and Software Engineering (FORGE), p. 57-68. (Acceptance ratio: 8/16=50%) BibTeX (Best Paper Award)