6 papers
Building Defect Prediction Models by Online Learning Considering Defect Overlooking
Nikolay Fedorov, Yuta Yamasaki, Masateru Tsunoda +5
Building defect prediction models based on online learning can enhance prediction accuracy. It continuously rebuilds a new prediction model, when a new data point is added. However…
Assessing the Security of GitHub Copilot Generated Code -- A Targeted Replication Study
Vahid Majdinasab, Michael Joshua Bishop, Shawn Rasheed +3
AI-powered code generation models have been developing rapidly, allowing developers to expedite code generation and thus improve their productivity. These models are trained on lar…
Software Defect Prediction by Online Learning Considering Defect Overlooking
Yuta Yamasaki, Nikolay Fedorov, Masateru Tsunoda +5
Building defect prediction models based on online learning can enhance prediction accuracy. It continuously rebuilds a new prediction model when adding a new data point. However, p…
On the Effect of Instrumentation on Test Flakiness
Shawn Rasheed, Jens Dietrich, Amjed Tahir
Test flakiness is a problem that affects testing and processes that rely on it. Several factors cause or influence the flakiness of test outcomes. Test execution order, randomness…
Flaky Test Sanitisation via On-the-Fly Assumption Inference for Tests with Network Dependencies
Jens Dietrich, Shawn Rasheed, Amjed Tahir
Flaky tests cause significant problems as they can interrupt automated build processes that rely on all tests succeeding and undermine the trustworthiness of tests. Numerous causes…
An Empirical Study of Flaky Tests in JavaScript
Negar Hashemi, Amjed Tahir, Shawn Rasheed
Flaky tests (tests with non-deterministic outcomes) can be problematic for testing efficiency and software reliability. Flaky tests in test suites can also significantly delay soft…