Codebert-nt: code naturalness via codebert

A Khanfir, M Jimenez, M Papadakis… - 2022 IEEE 22nd …, 2022 - ieeexplore.ieee.org
Much of recent software-engineering research has investigated the naturalness of code, the
fact that code, in small code snippets, is repetitive and can be predicted using statistical …

Learning test-mutant relationship for accurate fault localisation

J Kim, G An, R Feldt, S Yoo - Information and Software Technology, 2023 - Elsevier
Context: Automated fault localisation aims to assist developers in the task of identifying the
root cause of the fault by narrowing down the space of likely fault locations. Simulating …

Contextual Predictive Mutation Testing

K Jain, U Alon, A Groce, C Le Goues - … of the 31st ACM Joint European …, 2023 - dl.acm.org
Mutation testing is a powerful technique for assessing and improving test suite quality that
artificially introduces bugs and checks whether the test suites catch them. However, it is also …

Comparing and combining analysis-based and learning-based regression test selection

J Zhang, Y Liu, M Gligoric, O Legunsen… - Proceedings of the 3rd …, 2022 - dl.acm.org
Regression testing---rerunning tests on each code version to detect newly-broken
functionality---is important and widely practiced. But, regression testing is costly due to the …

Large Language Models for Equivalent Mutant Detection: How Far Are We?

Z Tian, H Shu, D Wang, X Cao, Y Kamei… - Proceedings of the 33rd …, 2024 - dl.acm.org
Mutation testing is vital for ensuring software quality. However, the presence of equivalent
mutants is known to introduce redundant cost and bias issues, hindering the effectiveness of …

FrMi: Fault-revealing Mutant Identification using killability severity

T Rostami, S Jalili - Information and Software Technology, 2023 - Elsevier
Context: Mutation testing is a powerful method used in software testing for various activities,
such as guidance for test case generation and test suite quality assessment. However, a …

An Exploratory Study on Using Large Language Models for Mutation Testing

B Wang, M Chen, Y Lin, M Papadakis… - arXiv preprint arXiv …, 2024 - arxiv.org
The question of how to generate high-utility mutations, to be used for testing purposes, forms
a key challenge in mutation testing literature.% Existing approaches rely either on human …

Predicting higher order mutation score based on machine learning

VN Do, QV Nguyen, TB Nguyen - Journal of Information and …, 2024 - Taylor & Francis
In software testing, the quality of the test suite plays a very important role for not only the
effectiveness of the testing but also the quality assurance of software. Mutation testing is …

Neural-MBFL: Improving Mutation-Based Fault Localization by Neural Mutation

B Du, B Han, H Liu, Z Chang, Y Liu… - 2024 IEEE 48th Annual …, 2024 - ieeexplore.ieee.org
As a key phase in software testing and debugging, fault localization can significantly
influence the efficiency of fixing software faults. Among the various techniques, Mutation …

Test Case Level Predictive Mutation Testing Combining PIE and Natural Language Features

R Xu, Y Shi, Z Su, X Wang, Z Yan… - 2023 30th Asia-Pacific …, 2023 - ieeexplore.ieee.org
Approaches predicting the results of mutation testing by machine learning have been
proposed to reduce the cost of mutation testing. The predictive approaches based on PIE …