Machine learning techniques for code smell detection: A systematic literature review and meta-analysis

MI Azeem, F Palomba, L Shi, Q Wang - Information and Software …, 2019 - Elsevier
Background: Code smells indicate suboptimal design or implementation choices in the
source code that often lead it to be more change-and fault-prone. Researchers defined …

A survey of flaky tests

O Parry, GM Kapfhammer, M Hilton… - ACM Transactions on …, 2021 - dl.acm.org
Tests that fail inconsistently, without changes to the code under test, are described as flaky.
Flaky tests do not give a clear indication of the presence of software bugs and thus limit the …

A snowballing literature study on test amplification

B Danglot, O Vera-Perez, Z Yu, A Zaidman… - Journal of Systems and …, 2019 - Elsevier
The adoption of agile approaches has put an increased emphasis on testing, resulting in
extensive test suites. These suites include a large number of tests, in which developers …

Understanding flaky tests: The developer's perspective

M Eck, F Palomba, M Castelluccio… - Proceedings of the 2019 …, 2019 - dl.acm.org
Flaky tests are software tests that exhibit a seemingly random outcome (pass or fail) despite
exercising unchanged code. In this work, we examine the perceptions of software …

Comparing heuristic and machine learning approaches for metric-based code smell detection

F Pecorelli, F Palomba, D Di Nucci… - 2019 IEEE/ACM 27th …, 2019 - ieeexplore.ieee.org
Code smells represent poor implementation choices performed by developers when
enhancing source code. Their negative impact on source code maintainability and …

What is the vocabulary of flaky tests?

G Pinto, B Miranda, S Dissanayake… - Proceedings of the 17th …, 2020 - dl.acm.org
Flaky tests are tests whose outcomes are non-deterministic. Despite the recent research
activity on this topic, no effort has been made on understanding the vocabulary of flaky tests …

Assessing and restoring reproducibility of Jupyter notebooks

J Wang, T Kuo, L Li, A Zeller - Proceedings of the 35th IEEE/ACM …, 2020 - dl.acm.org
Jupyter notebooks---documents that contain live code, equations, visualizations, and
narrative text---now are among the most popular means to compute, present, discuss and …

A large empirical assessment of the role of data balancing in machine-learning-based code smell detection

F Pecorelli, D Di Nucci, C De Roover… - Journal of Systems and …, 2020 - Elsevier
Code smells can compromise software quality in the long term by inducing technical debt.
For this reason, many approaches aimed at identifying these design flaws have been …

[PDF][PDF] On the distribution of test smells in open source Android applications: an exploratory study.

A Peruma, K Almalki, CD Newman, MW Mkaouer… - …, 2019 - fpalomba.github.io
The impact of bad programming practices, such as code smells, in production code has
been the focus of numerous studies in software engineering. Like production code, unit tests …

Not all bugs are the same: Understanding, characterizing, and classifying bug types

G Catolino, F Palomba, A Zaidman… - Journal of Systems and …, 2019 - Elsevier
Modern version control systems, eg, GitHub, include bug tracking mechanisms that
developers can use to highlight the presence of bugs. This is done by means of bug reports …