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Mohammad Rezaalipour
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Year
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
102019
AxMAP: Making Approximate Adders Aware of Input Patterns
M Rezaalipour, M Rezaalipour, M Dehyadegari, M Nazm Bojnordi
IEEE Transactions on Computers, 2020
72020
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
42018
An annotation-based approach for finding bugs in neural network programs
M Rezaalipour, CA Furia
Journal of Systems and Software 201, 111669, 2023
22023
Test-case generation for finding neural network bugs
M Rezaalipour, CA Furia
arXiv 2112, 2021
12021
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
An Empirical Study of Fault Localization in Python Programs
M Rezaalipour, CA Furia
arXiv preprint arXiv:2305.19834, 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
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Articles 1–9