MaLTeSQuE 2019 – Proceedings

3rd ACM SIGSOFT International Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE 2019)

Frontmatter

Testing and Debugging

Leveraging Mutants for Automatic Prediction of Metamorphic Relations using Machine Learning
Aravind Nair, Karl Meinke, and Sigrid Eldh
(KTH, Sweden; Ericsson, Sweden)

Publisher's Version

SZZ Unleashed: An Open Implementation of the SZZ Algorithm - Featuring Example Usage in a Study of Just-in-Time Bug Prediction for the Jenkins Project
Markus Borg, Oscar Svensson, Kristian Berg, and Daniel Hansson
(RISE SICS, Sweden; Lund University, Sweden; Verifyter, Sweden)

Publisher's Version Info

On the Role of Data

Risk-Based Data Validation in Machine Learning-Based Software Systems
Harald Foidl and Michael Felderer
(University of Innsbruck, Austria)

Publisher's Version

On the Role of Data Balancing for Machine Learning-Based Code Smell Detection
Fabiano Pecorelli, Dario Di Nucci, Coen De Roover, and Andrea De Lucia
(University of Salerno, Italy; Vrije Universiteit Brussel, Belgium)

Publisher's Version

Quality Attributes

Classifying Non-functional Requirements using RNN Variants for Quality Software Development
Md. Abdur Rahman, Md. Ariful Haque, Md. Nurul Ahad Tawhid, and Md. Saeed Siddik
(University of Dhaka, Bangladesh)

Publisher's Version

A Machine Learning Based Automatic Folding of Dynamically Typed Languages
Nickolay Viuginov and Andrey Filchenkov
(JetBrains, Russia; ITMO University, Russia)

Publisher's Version

Towards Surgically-Precise Technical Debt Estimation: Early Results and Research Roadmap
Valentina Lenarduzzi, Antonio Martini, Davide Taibi, and Damian Andrew Tamburri
(Tampere University, Finland; University of Oslo, Norway; Eindhoven University of Technology, Netherlands)

Publisher's Version

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