Blogs (61) >>
Wed 18 Jul 2018 15:00 - 15:30 at Bangkok - Session #2 Chair(s): Artem Pelenitsyn

This paper discusses code anomalies — code fragments that are written in some way that is not typical for the programming language community. Such code fragments are useful to language creators as performance tests or they could provide insights on how to improve the language. With Kotlin as the target language, we discuss how the task of detecting code anomalies for a very large codebase could be solved using well-known anomaly detection techniques. We outline and discuss approaches to obtain code vector representation and to perform anomaly detection on such vectorized data. The paper concludes with our preliminary results.

Wed 18 Jul
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14:00 - 15:30
Session #2ML4PL at Bangkok
Chair(s): Artem PelenitsynCzech Technical University in Prague
14:00
30m
Talk
Buffer Overflow Detection for C Programs is Hard to Learn
ML4PL
Cristina CifuentesOracle Labs, Yang ZhaoOracle Labs, Xingzhong DuOracle Labs, Paddy Krishnan
14:30
30m
Talk
Generating Software Adaptations using Machine Learning
ML4PL
Nicolás CardozoUniversidad de los Andes, Ivana DusparicTrinity College Dublin, Ireland
15:00
30m
Talk
Detecting anomalies in Kotlin code
ML4PL
Timofey Bryksin, Victor PetukhovITMO University, Kirill SmirenkoSaint Petersburg State University, Nikita PovarovJetBrains