An Approach to Generate Effective Fault Localization Methods for Programs B Bagheri, M Rezaalipour, M Vahidi-Asl 8th IPM International Conference on Fundamentals of Software Engineering …, 2019 | 10 | 2019 |
AxMAP: Making Approximate Adders Aware of Input Patterns M Rezaalipour, M Rezaalipour, M Dehyadegari, M Nazm Bojnordi IEEE Transactions on Computers, 2020 | 7 | 2020 |
Arselda: An Improvement on Adaptive Random Testing by Adaptive Region Selection M Rezaalipour, L Talebsafa, M Vahidi-Asl 2018 8th International Conference on Computer and Knowledge Engineering …, 2018 | 4 | 2018 |
An annotation-based approach for finding bugs in neural network programs M Rezaalipour, CA Furia Journal of Systems and Software 201, 111669, 2023 | 2 | 2023 |
An Empirical Study of Fault Localization in Python Programs M Rezaalipour, CA Furia arXiv preprint arXiv:2305.19834, 2023 | 1 | 2023 |
Test-case generation for finding neural network bugs M Rezaalipour, CA Furia arXiv 2112, 2021 | 1 | 2021 |
FauxPy: A Fault Localization Tool for Python M Rezaalipour, CA Furia arXiv preprint arXiv:2404.18596, 2024 | | 2024 |
Doctor Code: A machine learning-based approach to program repair S Moosavi, M Vahidi-Asl, H Haghighi, M Rezaalipour Scientia Iranica 31 (2), 83-102, 2024 | | 2024 |
aNNoTest: An Annotation-based Test Generation Tool for Neural Network Programs M Rezaalipour, CA Furia 2023 IEEE International Conference on Software Maintenance and Evolution …, 2023 | | 2023 |
IDrAx: A tool-chain for designing efficient approximate adders M Rezaalipour, M Rezaalipour, S Tajasob, M Dehyadegari Microelectronics Journal 90, 222-231, 2019 | | 2019 |