Zero Shot Learning based Alternatives for Class Imbalanced Learning Problem in Enterprise Software Defect Analysis
Pages 140 - 141
Abstract
Software defect reports are an important type of text data for enterprises as they provide actionable information for improving software quality. Identifying the software defect type automatically can greatly enhance and expedite defect management. Class imbalance is a real-life problem in enterprise software defect classification task and adversely affects the automation effort. We show that zero shot learning based technique can be a good alternative to the well-known supervised learning and SMOTE techniques.
References
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Nitesh V Chawla, Kevin W Bowyer, Lawrence O Hall, and W Philip Kegelmeyer. 2002. SMOTE: synthetic minority over-sampling technique. Journal of artificial intelligence research 16 (2002), 321--357.
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IEEE. 2009. IEEE Standard 1044-2009 Classification for Software Anomalies.
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Sangameshwar Patil. 2017. Concept based Classification of Software Defect Reports. In Proc. of 14th International Conference on Mining Software Repositories (MSR). IEEE/ACM.
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Sangameshwar Patil and B. Ravindran. 2020. Predicting software defect type using concept-based classification. Empirical Software Engineering 25, 2 (2020), 1341--1378.
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Sangameshwar Patil and B. Ravindran. 2023. Tackling the Class Imbalance Challenge for Software Defect Type Classification using Knowledge Augmented Method. In Second Workshop on Knowledge Augmented Methods for Natural Language Processing, in conjunction with the Knowledge Discovery from Data conference (KNLP at KDD'23). ACM, Long Beach, CA, USA. https://knowledge-nlp.github.io/kdd2023/papers/Patil4.pdf
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Ferdian Thung, Xuan-Bach Le D., and David Lo. 2015. Active Semi-Supervised Defect Categorization. In Proc. of IEEE 23rd International Conference on Program Comprehension (ICPC). 60--70.
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Ferdian Thung, David Lo, and Lingxiao Jiang. 2012. Automatic defect categorization. In Proc. of 19th Working Conference on Reverse Engineering (WCRE). IEEE, 205--214.
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Index Terms
- Zero Shot Learning based Alternatives for Class Imbalanced Learning Problem in Enterprise Software Defect Analysis
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Published In
April 2024
788 pages
ISBN:9798400705878
DOI:10.1145/3643991
- Chair:
- Diomidis Spinellis,
- Program Chair:
- Alberto Bacchelli,
- Program Co-chair:
- Eleni Constantinou
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Published: 02 July 2024
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MSR '24
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MSR '24: 21st International Conference on Mining Software Repositories
April 15 - 16, 2024
Lisbon, Portugal
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