Computational Intelligence for Software Engineering Laboratory
We optimise and improve software through the use of machine intelligence.
- Donghwan Shin, Shin Yoo, and Doo-hwan Bae, A theoretical and empirical study of diversity-aware mutation adequacy criterion, IEEE Transactions on Software Engineering, 2017.
- Jinhan Kim, Junhwi Kim, and Shin Yoo, GPGPGPU: Evaluation of Parallelisation of Genetic Programming using GPGPU, SSBSE 2017
- Seongmin Lee and Shin Yoo, Hyperheuristic Observation Based Slicing of Guava, SSBSE 2017
- Junhwi Kim, Byeonghyeon You, Minhyuk Kwon, Phil McMinn, and Shin Yoo, Evaluating CAVM: a new search-based test data generation tool for C, SSBSE 2017.
- Dahyun Kang, Jeongju Sohn, and Shin Yoo, Empirical evaluation of conditional operators in GP based fault localization, GECCO 2017.
- Jeongju Sohn and Shin Yoo, FLUCCS: Using Code and Change Metrics to Improve Fault Localisation, ISSTA 2017.