Mutation testing advances: an analysis and survey
Mutation testing realizes the idea of using artificial defects to support testing activities.
Mutation is typically used as a way to evaluate the adequacy of test suites, to guide the …
Mutation is typically used as a way to evaluate the adequacy of test suites, to guide the …
Deepmutation: Mutation testing of deep learning systems
Deep learning (DL) defines a new data-driven programming paradigm where the internal
system logic is largely shaped by the training data. The standard way of evaluating DL …
system logic is largely shaped by the training data. The standard way of evaluating DL …
Toga: A neural method for test oracle generation
Testing is widely recognized as an important stage of the software development lifecycle.
Effective software testing can provide benefits such as bug finding, preventing regressions …
Effective software testing can provide benefits such as bug finding, preventing regressions …
Explainable automated debugging via large language model-driven scientific debugging
Automated debugging techniques have the potential to reduce developer effort in
debugging. However, while developers want rationales for the provided automatic …
debugging. However, while developers want rationales for the provided automatic …
Predictive mutation testing
Mutation testing is a powerful methodology for evaluating test suite quality. In mutation
testing, a large number of mutants are generated and executed against the test suite to …
testing, a large number of mutants are generated and executed against the test suite to …
An empirical study of flaky tests in python
Tests that cause spurious failures without any code changes, ie, flaky tests, hamper
regression testing, increase maintenance costs, may shadow real bugs, and decrease trust …
regression testing, increase maintenance costs, may shadow real bugs, and decrease trust …
Are mutation scores correlated with real fault detection? a large scale empirical study on the relationship between mutants and real faults
Empirical validation of software testing studies is increasingly relying on mutants. This
practice is motivated by the strong correlation between mutant scores and real fault …
practice is motivated by the strong correlation between mutant scores and real fault …
[PDF][PDF] Unifying the perspectives of nlp and software engineering: A survey on language models for code
Z Zhang, C Chen, B Liu, C Liao, Z Gong… - arXiv preprint arXiv …, 2023 - simg.baai.ac.cn
In this work we systematically review the recent advancements in code processing with
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …
On the effectiveness of manual and automatic unit test generation: ten years later
Good unit tests play a paramount role when it comes to foster and evaluate software quality.
However, writing effective tests is an extremely costly and time consuming practice. To …
However, writing effective tests is an extremely costly and time consuming practice. To …
Learning to construct better mutation faults
Mutation faults are the core of mutation testing and have been widely used in many other
software testing and debugging tasks. Hence, constructing high-quality mutation faults is …
software testing and debugging tasks. Hence, constructing high-quality mutation faults is …