Improved Evaluation of Automatic Source Code Summarisation

Phillips, J., Bowes, D., El-Haj, M. & Hall, T., 7/12/2022, 2nd Wokshop on Natural Language Generation, Evaluation and Metrics: Proceedings of the Workshop. Stroudsberg, PA.: Association for Computational Linguistics (ACL Anthology), p. 326-335 10 p.

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Improving the Performance of Code Vulnerability Prediction using Abstract Syntax Tree Information

Debeyan, F., Hall, T. & Bowes, D., 17/11/2022, PROMISE 2022: Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering. McIntosh, S., Shang, W. & Perez, G. R. (eds.). New York: ACM, p. 2-11 10 p.

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Towards Developer-Centered Automatic Program Repair: Findings from Bloomberg

Winter, E., Nowack, V., Bowes, D., Counsell, S., Hall, T., Haraldsson, S., Woodward, J., Kirbas, S., Windells, E., McBello, O., Atakishiyev, A., Kells, K. & Pagano, M., 9/11/2022, ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) . New York: ACM

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Some automatically generated patches are more likely to be correct than others: an analysis of Defects4J patch features

Bennett, G., Hall, T. & Bowes, D., 26/10/2022, Proceedings - International Workshop on Automated Program Repair, APR 2022. New York: ACM, p. 46-52 7 p.

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Expanding Fix Patterns to Enable Automatic Program Repair

Nowack, V., Bowes, D., Counsell, S., Hall, T., Haraldsson, S., Winter, E. & Woodward, J., 11/02/2022, 2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE). Jin, Z., Li, X., Xiang, J., Mariani, L., Liu, T., Yu, X. & Ivaki, N. (eds.). IEEE Computer Society Press, p. 12-23 12 p. (2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE)).

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Using Machine Learning to Recognise Novice and Expert Programmers

Lee, C. H. & Hall, T., 23/11/2021, Product-Focused Software Process Improvement - 22nd International Conference, PROFES 2021, Proceedings: 22nd International Conference, PROFES 2021, Turin, Italy, November 26, 2021, Proceedings. Ardito, L., Jedlitschka, A., Morisio, M. & Torchiano, M. (eds.). Cham: Springer, p. 199-206 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13126 LNCS).

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BugVis: Commit slicing for fault visualisation

Bowes, D., Petric, J. & Hall, T., 5/10/2020, ICPC '20: Proceedings of the 28th International Conference on Program Comprehension. New York: ACM, p. 436-440 5 p.

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Zones of pain: Visualising the relationship between software architecture and defects

Petrić, J., Hall, T. & Bowes, D., 31/08/2020, Quality of Information and Communications Technology: 13th International Conference, QUATIC 2020, Faro, Portugal, September 9–11, 2020, Proceedings. Shepperd, M., Brito e Abreu, F., Rodrigues da Silva, A. & Pérez-Castillo, R. (eds.). Cham: Springer Science and Business Media Deutschland GmbH, p. 135-143 9 p. (Communications in Computer and Information Science; vol. 1266).

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Human Factors in the Study of Automatic Software Repair: Future Directions for Research with Industry

Winter, E., Bowes, D., Counsell, S., Hall, T., Haraldsson, S., Nowack, V. & Woodward, J., 6/07/2020, Proceedings - 2020 IEEE/ACM 42nd International Conference on Software Engineering Workshops, ICSEW 2020. New York: Association for Computing Machinery, Inc, p. 285-286 2 p. (Proceedings - 2020 IEEE/ACM 42nd International Conference on Software Engineering Workshops, ICSEW 2020).

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Which Software Faults Are Tests Not Detecting?

Petric, J., Hall, T. & Bowes, D., 15/04/2020, PROCEEDINGS of EASE 2020: Evaluation and Assessment in Software Engineering. New York: ACM, p. 160-169 10 p.

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How Effectively Is Defective Code Actually Tested? An Analysis of JUnit Tests in Seven Open Source Systems

Petric, J., Hall, T. & Bowes, D., 10/10/2018, Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering. New York, NY, USA: ACM, p. 42-51 10 p. (PROMISE'18).

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Mining communication patterns in software development: A GitHub analysis

Ortu, M., Hall, T., Marchesi, M., Tonelli, R., Bowes, D. & Destefanis, G., 10/10/2018, PROMISE'18 Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering. New York: ACM, p. 70-79 10 p.

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Code cleaning for software defect prediction: A cautionary tale

Shippey, T., Bowes, D., Counsell, S. & Hall, T., 29/08/2018, 2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). IEEE, p. 239-243 5 p.

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The relationship between evolutionary coupling and defects in large industrial software (journal-first abstract)

Kirbas, S., Caglayan, B., Hall, T., Counsell, S., Bowes, D., Sen, A. & Bener, A., 2/04/2018, 25th IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 471 1 p.

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Getting defect prediction into industrial practice: The ELFF tool

Bowes, D., Counsell, S., Hall, T., Petric, J. & Shippey, T., 14/11/2017, Proceedings - 2017 IEEE 28th International Symposium on Software Reliability Engineering Workshops, ISSREW 2017. Institute of Electrical and Electronics Engineers Inc., p. 44-47 4 p. 8109247

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Assert use and defectiveness in industrial code

Counsell, S., Hall, T., Shippey, T., Bowes, D., Tahir, A. & MacDonell, S., 14/11/2017, Proceedings - 2017 IEEE 28th International Symposium on Software Reliability Engineering Workshops, ISSREW 2017. Institute of Electrical and Electronics Engineers Inc., p. 20-23 4 p. 8109241

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How Good Are My Tests?

Bowes, D., Hall, T., Petrić, J., Shippey, T. & Turhan, B., 3/07/2017, 2017 IEEE/ACM 8th Workshop on Emerging Trends in Software Metrics (WETSoM). IEEE Computer Society, p. 9-14 6 p. 7968009. (2017 IEEE/ACM 8th Workshop on Emerging Trends in Software Metrics (WETSoM)).

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Building an Ensemble for Software Defect Prediction Based on Diversity Selection

Petrić, J., Bowes, D., Hall, T., Christianson, B. & Baddoo, N., 8/09/2016, ESEM '16 Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. New York: Association for Computing Machinery, Inc, 10 p. 46

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So You Need More Method Level Datasets for Your Software Defect Prediction? Voilà!

Shippey, T., Hall, T., Counsell, S. & Bowes, D., 8/09/2016, ESEM '16 Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. New York: IEEE Computer Society, 6 p. 12

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Mutation-aware fault prediction

Bowes, D., Hall, T., Harman, M., Jia, Y., Sarro, F. & Wu, F., 18/07/2016, ISSTA 2016 Proceedings of the 25th International Symposium on Software Testing and Analysis. New York: Association for Computing Machinery, Inc, p. 330-341 12 p.

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The Jinx on the NASA software defect data sets

Petrić, J., Bowes, D., Hall, T., Christianson, B. & Baddoo, N., 1/06/2016, EASE '16 Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering. New York: Association for Computing Machinery, Inc, 5 p. 13

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Different classifiers find different defects although with different level of consistency

Bowes, D., Hall, T. & Petrić, J., 21/10/2015, PROMISE '15 Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering. New York: Association for Computing Machinery, Inc, 10 p.

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What is the impact of imbalance on software defect prediction performance?

Mahmood, Z., Bowes, D., Lane, P. C. R. & Hall, T., 21/10/2015, PROMISE '15 Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering. New York: Association for Computing Machinery, Inc, 4

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The inconsistent measurement of Message Chains

Bowes, D., Randall, D. & Hall, T., 2013, 2013 4th International Workshop on Emerging Trends in Software Metrics (WETSoM). IEEE, p. 62-68 7 p.

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A mapping study of software code cloning

Shippey, T., Bowes, D., Chrisianson, B. & Hall, T., 2012, 16th International Conference on Evaluation & Assessment in Software Engineering (EASE 2012). IEEE, p. 274-278 5 p.

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