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- Publications
- Influence
Predicting faults using the complexity of code changes
- A. Hassan
- Computer Science
- IEEE 31st International Conference on Software…
- 16 May 2009
Predicting the incidence of faults in code has been commonly associated with measuring complexity. In this paper, we propose complexity metrics that are based on the code change process instead of on… Expand
What are developers talking about? An analysis of topics and trends in Stack Overflow
- Anton Barua, S. W. Thomas, A. Hassan
- Computer Science
- Empirical Software Engineering
- 1 June 2014
Programming question and answer (Q&A) websites, such as Stack Overflow, leverage the knowledge and expertise of users to provide answers to technical questions. Over time, these websites turn into… Expand
A large-scale empirical study of just-in-time quality assurance
- Yasutaka Kamei, Emad Shihab, +4 authors N. Ubayashi
- Computer Science
- IEEE Transactions on Software Engineering
- 1 June 2013
Defect prediction models are a well-known technique for identifying defect-prone files or packages such that practitioners can allocate their quality assurance efforts (e.g., testing and code… Expand
Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models
- Baljinder Ghotra, Shane McIntosh, A. Hassan
- Computer Science
- IEEE/ACM 37th IEEE International Conference on…
- 16 May 2015
Defect prediction models help software quality assurance teams to effectively allocate their limited resources to the most defect-prone software modules. A variety of classification techniques have… Expand
Predicting change propagation in software systems
Software systems contain entities, such as functions and variables, which are related to each other. As a software system evolves to accommodate new features and repair bugs, changes occur to these… Expand
Automated Parameter Optimization of Classification Techniques for Defect Prediction Models
- C. Tantithamthavorn, Shane McIntosh, A. Hassan, K. Matsumoto
- Computer Science
- IEEE/ACM 38th International Conference on…
- 14 May 2016
Defect prediction models are classifiers that are trained to identify defect-prone software modules. Such classifiers have configurable parameters that control their characteristics (e.g., the number… Expand
Clustering WSDL Documents to Bootstrap the Discovery of Web Services
- Khalid Elgazzar, A. Hassan, P. Martin
- Computer Science
- IEEE International Conference on Web Services
- 5 July 2010
The increasing use of the Web for everyday tasks is making Web services an essential part of the Internet customer's daily life. Users query the Internet for a required Web service and get back a set… Expand
An Empirical Comparison of Model Validation Techniques for Defect Prediction Models
- C. Tantithamthavorn, Shane McIntosh, A. Hassan, K. Matsumoto
- Computer Science
- IEEE Transactions on Software Engineering
- 2017
Defect prediction models help software quality assurance teams to allocate their limited resources to the most defect-prone modules. Model validation techniques, such as <inline-formula><tex-math… Expand
The impact of code review coverage and code review participation on software quality: a case study of the qt, VTK, and ITK projects
- Shane McIntosh, Yasutaka Kamei, B. Adams, A. Hassan
- Computer Science
- MSR
- 31 May 2014
Software code review, i.e., the practice of having third-party team members critique changes to a software system, is a well-established best practice in both open source and proprietary software… Expand
Comparison of clustering algorithms in the context of software evolution
- J. Wu, A. Hassan, R. Holt
- Computer Science
- 21st IEEE International Conference on Software…
- 25 September 2005
To aid software analysis and maintenance tasks, a number of software clustering algorithms have been proposed to automatically partition a software system into meaningful subsystems or clusters.… Expand