4 citations · 5 across the 4 of their papers we have counts for
9 papers
Improving Test Case Generation for REST APIs Through Hierarchical Clustering
Dimitri Stallenberg, Mitchell Olsthoorn, Annibale Panichella
With the ever-increasing use of web APIs in modern-day applications, it is becoming more important to test the system as a whole. In the last decade, tools and approaches have been…
Hybrid Multi-level Crossover for Unit Test Case Generation
Mitchell Olsthoorn, Pouria Derakhshanfar, Annibale Panichella
State-of-the-art search-based approaches for test case generation work at test case level, where tests are represented as sequences of statements. These approaches make use of gene…
Multi-objective Test Case Selection Through Linkage Learning-based Crossover
Mitchell Olsthoorn, Annibale Panichella
Test Case Selection (TCS) aims to select a subset of the test suite to run for regression testing. The selection is typically based on past coverage and execution cost data. Resear…
What Are We Really Testing in Mutation Testing for Machine Learning? A Critical Reflection
Annibale Panichella, Cynthia C. S. Liem
Mutation testing is a well-established technique for assessing a test suite's quality by injecting artificial faults into production code. In recent years, mutation testing has bee…
Search-Based Software Re-Modularization: A Case Study at Adyen
Casper Schröder, Adriaan van der Feltz, Annibale Panichella +1
Deciding what constitutes a single module, what classes belong to which module or the right set of modules for a specific software system has always been a challenging task. The pr…
Run, Forest, Run? On Randomization and Reproducibility in Predictive Software Engineering
Cynthia C. S. Liem, Annibale Panichella
Machine learning (ML) has been widely used in the literature to automate software engineering tasks. However, ML outcomes may be sensitive to randomization in data sampling mechani…