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MaLTeSQuE@ESEC/SIGSOFT FSE
2019
2022
2019
2022
Keyphrases
Publications
2022
Nikolaos Nikolaidis
,
Dimitrios Zisis
,
Apostolos Ampatzoglou
,
Nikolaos Mittas
,
Alexander Chatzigeorgiou
Using machine learning to guide the application of software refactorings: a preliminary exploration.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2022)
Chao Liu
,
Qiaoluan Xie
,
Yong Li
,
Yang Xu
,
Hyun-Deok Choi
DeepCrash: deep metric learning for crash bucketing based on stack trace.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2022)
Matthew Yit Hang Yeow
,
Chun Yong Chong
,
Mei Kuan Lim
On the application of machine learning models to assess and predict software reusability.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2022)
Niranjan Hasabnis
Are machine programming systems using right source-code measures to select code repositories?
MaLTeSQuE@ESEC/SIGSOFT FSE
(2022)
Srinivasan Sengamedu
,
Hangqi Zhao
Neural language models for code quality identification.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2022)
Yuriy Brun
The promise and perils of using machine learning when engineering software (keynote paper).
MaLTeSQuE@ESEC/SIGSOFT FSE
(2022)
Proceedings of the 6th International Workshop on Machine Learning Techniques for Software Quality Evaluation, MaLTeSQuE 2022, Singapore, Singapore, 18 November 2022
MaLTeSQuE@ESEC/SIGSOFT FSE
(2022)
2021
MaLTeSQuE@ESEC/SIGSOFT FSE 2021: Proceedings of the 5th International Workshop on Machine Learning Techniques for Software Quality Evolution, Athens, Greece, 23 August 2021
MaLTeSQuE@ESEC/SIGSOFT FSE
(2021)
Francesco Lomio
,
Sampsa Jurvansuu
,
Davide Taibi
Metrics selection for load monitoring of service-oriented system.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2021)
Mikhail Pravilov
,
Egor Bogomolov
,
Yaroslav Golubev
,
Timofey Bryksin
Unsupervised learning of general-purpose embeddings for code changes.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2021)
Ignacio Nuñez Norambuena
,
Alexandre Bergel
Building a bot for automatic expert retrieval on discord.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2021)
Manuel De Stefano
,
Fabiano Pecorelli
,
Fabio Palomba
,
Andrea De Lucia
Comparing within- and cross-project machine learning algorithms for code smell detection.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2021)
Valeria Pontillo
,
Fabio Palomba
,
Filomena Ferrucci
Toward static test flakiness prediction: a feasibility study.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2021)
Sophie Fortz
,
Paul Temple
,
Xavier Devroey
,
Patrick Heymans
,
Gilles Perrouin
VaryMinions: leveraging RNNs to identify variants in event logs.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2021)
2020
Proceedings of the 4th ACM SIGSOFT International Workshop on Machine Learning Techniques for Software Quality Evaluation, MaLTeSQuE@ESEC/SIGSOFT FSE 2020, Virtual Event, USA, November 13, 2020.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2020)
Stefano Dalla Palma
,
Majid Mohammadi
,
Dario Di Nucci
,
Damian A. Tamburri
Singling the odd ones out: a novelty detection approach to find defects in infrastructure-as-code.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2020)
Roman Vasiliev
,
Dmitrij V. Koznov
,
George A. Chernishev
,
Aleksandr Khvorov
,
Dmitry V. Luciv
,
Nikita Povarov
TraceSim: a method for calculating stack trace similarity.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2020)
Francesco Lomio
,
Diego Martínez Baselga
,
Sergio Moreschini
,
Heikki Huttunen
,
Davide Taibi
RARE: a labeled dataset for cloud-native memory anomalies.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2020)
Martin Steinhauer
,
Fabio Palomba
Speeding up the data extraction of machine learning approaches: a distributed framework.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2020)
Nemania Borovits
,
Indika Kumara
,
Parvathy Krishnan
,
Stefano Dalla Palma
,
Dario Di Nucci
,
Fabio Palomba
,
Damian A. Tamburri
,
Willem-Jan van den Heuvel
DeepIaC: deep learning-based linguistic anti-pattern detection in IaC.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2020)
Savanna Lujan
,
Fabiano Pecorelli
,
Fabio Palomba
,
Andrea De Lucia
,
Valentina Lenarduzzi
A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2020)
2019
Harald Foidl
,
Michael Felderer
Risk-based data validation in machine learning-based software systems.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2019)
Nickolay Viuginov
,
Andrey Filchenkov
A machine learning based automatic folding of dynamically typed languages.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2019)
Aravind Nair
,
Karl Meinke
,
Sigrid Eldh
Leveraging mutants for automatic prediction of metamorphic relations using machine learning.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2019)
Md. Abdur Rahman
,
Md. Ariful Haque
,
Md. Nurul Ahad Tawhid
,
Md. Saeed Siddik
Classifying non-functional requirements using RNN variants for quality software development.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2019)
Markus Borg
,
Oscar Svensson
,
Kristian Berg
,
Daniel Hansson
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.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2019)
Proceedings of the 3rd ACM SIGSOFT International Workshop on Machine Learning Techniques for Software Quality Evaluation, MaLTeSQuE@ESEC/SIGSOFT FSE 2019, Tallinn, Estonia, August 27, 2019.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2019)
Valentina Lenarduzzi
,
Antonio Martini
,
Davide Taibi
,
Damian Andrew Tamburri
Towards surgically-precise technical debt estimation: early results and research roadmap.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2019)
Fabiano Pecorelli
,
Dario Di Nucci
,
Coen De Roover
,
Andrea De Lucia
On the role of data balancing for machine learning-based code smell detection.
MaLTeSQuE@ESEC/SIGSOFT FSE
(2019)