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On the Frontiers of Software Science and Software Engineering
Frontiers in Computer Science, 2022 Advances in software engineering, software science, computational intelligence, and intelligent mathematics have led to the establishment of Frontiers in Computer Science—Software (FCSS).
Yingxu Wang
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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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Software Engineering in Australasia
ACM SIGSOFT Software Engineering Notes, 2021 Six months ago an important call was made for researchers globally to provide insights into the way Software Engineering is done in their region. Heeding this call, we hereby outline the position Software Engineering in Australasia (New Zealand and Australia).
LICORISH, Sherlock A. +7 more
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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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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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Explainable AI for Software Engineering [PDF]
International Conference on Automated Software Engineering, 2020 The success of software engineering projects largely depends on complex decision-making. For example, which tasks should a developer do first, who should perform this task, is the software of high quality, is a software system reliable and resilient ...
C. Tantithamthavorn +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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Structuring meaningful bug‐fixing patches to fix software defect
IET Software, 2023 Currently, software projects require a significant amount of time, effort and other resources to be invested in software testing to reduce the number of code defects.
Hui Li +4 more
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Brief review of classical Effort Estimation models for Software development projects
Selecciones Matemáticas, 2023 A critical synthesis on the most representative models for software development project effort estimation is provided. This work is a basis for a discussion about the methodological and practical challenges which entail the effort estimation field ...
Diego Bravo-Estrada, Roxana López-Cruz
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