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Guidelines for conducting and reporting case study research in software engineering
Empirical Software Engineering, 2009 Case study is a suitable research methodology for software engineering research since it studies contemporary phenomena in its natural context. However, the understanding of what constitutes a case study varies, and hence the quality of the resulting ...
P. Runeson, Martin Höst
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Requirements Engineering in Machine Learning Projects
IEEE Access, 2023 Over the last decade, machine learning methods have revolutionized a large number of domains and provided solutions to many problems that people could hardly solve in the past. The availability of large amounts of data, powerful processing architectures,
Ana Gjorgjevikj +3 more
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A Survey on Deep Learning for Software Engineering [PDF]
ACM Computing Surveys, 2020 In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)” and an improved model training method to break the bottleneck of neural network development.
Yanming Yang +3 more
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Engineering software correctness [PDF]
Proceedings of the 2005 workshop on Functional and declarative programming in education, 2005 AbstractDesign and quality are fundamental themes in engineering education. Functional programming builds software from small components, a central element of good design, and facilitates reasoning about correctness, an important aspect of quality. Software engineering courses that employ functional programming provide a platform for educating students
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Quantum Software Engineering: Roadmap and Challenges Ahead [PDF]
ACM Transactions on Software Engineering and MethodologyAs quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective—key qualities of any industry-grade software—mature software engineering ...
J. M. Murillo +15 more
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Adoption and Effects of Software Engineering Best Practices in Machine Learning [PDF]
International Symposium on Empirical Software Engineering and Measurement, 2020 Background. The increasing reliance on applications with machine learning (ML) components calls for mature engineering techniques that ensure these are built in a robust and future-proof manner. Aim.
A. Serban +3 more
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Topic modeling in software engineering research
Empirical Software Engineering, 2021 Topic modeling using models such as Latent Dirichlet Allocation (LDA) is a text mining technique to extract human-readable semantic “topics” (i.e., word clusters) from a corpus of textual documents.
Camila Costa Silva +2 more
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Heterogeneous Cross-Project Defect Prediction via Optimal Transport
IEEE Access, 2023 Heterogeneous cross-project defect prediction (HCPDP) aims to learn a prediction model from a heterogeneous source project and then apply the model to a target project.
Xing Zong +5 more
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A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering [PDF]
IEEE Transactions on Software Engineering, 2020 Chatbots are envisioned to dramatically change the future of Software Engineering, allowing practitioners to chat and inquire about their software projects and interact with different services using natural language.
Ahmad Abdellatif +3 more
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A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research [PDF]
ACM Transactions on Software Engineering and Methodology, 2020 An increasingly popular set of techniques adopted by software engineering (SE) researchers to automate development tasks are those rooted in the concept of Deep Learning (DL).
Cody Watson +4 more
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