Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation
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(FIVE YEARS 6)

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(FIVE YEARS 1)

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9781450381246

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DeepIaC: deep learning-based linguistic anti-pattern detection in IaC

Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation ◽

10.1145/3416505.3423564 ◽

2020 ◽

Author(s):

Nemania Borovits ◽

Indika Kumara ◽

Parvathy Krishnan ◽

Stefano Dalla Palma ◽

Dario Di Nucci ◽

...

Keyword(s):

Deep Learning ◽

Pattern Detection

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TraceSim: a method for calculating stack trace similarity

Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation ◽

10.1145/3416505.3423561 ◽

2020 ◽

Author(s):

Roman Vasiliev ◽

Dmitrij Koznov ◽

George Chernishev ◽

Aleksandr Khvorov ◽

Dmitry Luciv ◽

...

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RARE: a labeled dataset for cloud-native memory anomalies

Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation ◽

10.1145/3416505.3423560 ◽

2020 ◽

Cited By ~ 1

Author(s):

Francesco Lomio ◽

Diego Martínez Baselga ◽

Sergio Moreschini ◽

Heikki Huttunen ◽

Davide Taibi

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Speeding up the data extraction of machine learning approaches: a distributed framework

Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation ◽

10.1145/3416505.3423562 ◽

2020 ◽

Author(s):

Martin Steinhauer ◽

Fabio Palomba

Keyword(s):

Machine Learning ◽

Data Extraction ◽

Learning Approaches ◽

Distributed Framework

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Singling the odd ones out: a novelty detection approach to find defects in infrastructure-as-code

Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation ◽

10.1145/3416505.3423563 ◽

2020 ◽

Author(s):

Stefano Dalla Palma ◽

Majid Mohammadi ◽

Dario Di Nucci ◽

Damian A. Tamburri

Keyword(s):

Novelty Detection ◽

Detection Approach

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A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction

Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation ◽

10.1145/3416505.3423559 ◽

2020 ◽

Author(s):

Savanna Lujan ◽

Fabiano Pecorelli ◽

Fabio Palomba ◽

Andrea De Lucia ◽

Valentina Lenarduzzi

Keyword(s):

Static Analysis ◽

Code Smell ◽

Preliminary Study

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Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality EvaluationLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By ACM

DeepIaC: deep learning-based linguistic anti-pattern detection in IaC

TraceSim: a method for calculating stack trace similarity

RARE: a labeled dataset for cloud-native memory anomalies

Speeding up the data extraction of machine learning approaches: a distributed framework

Singling the odd ones out: a novelty detection approach to find defects in infrastructure-as-code

A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction

Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation
Latest Publications