Testing scientific software: A systematic literature review U Kanewala, JM Bieman Information and software technology 56 (10), 1219-1232, 2014 | 191 | 2014 |
Predicting metamorphic relations for testing scientific software: a machine learning approach using graph kernels U Kanewala, JM Bieman, A Ben‐Hur Software testing, verification and reliability 26 (3), 245-269, 2016 | 147 | 2016 |
Using machine learning techniques to detect metamorphic relations for programs without test oracles U Kanewala, JM Bieman 2013 IEEE 24th International Symposium on Software Reliability Engineering …, 2013 | 126 | 2013 |
Techniques for testing scientific programs without an oracle U Kanewala, JM Bieman 2013 5th International Workshop on Software Engineering for Computational …, 2013 | 53 | 2013 |
Automated test oracles: State of the art, taxonomies, and trends RAP Oliveira, U Kanewala, PA Nardi Advances in computers 95, 113-199, 2014 | 48 | 2014 |
Using semi-supervised learning for predicting metamorphic relations B Hardin, U Kanewala Proceedings of the 3rd International Workshop on Metamorphic Testing, 14-17, 2018 | 34 | 2018 |
Techniques for automatic detection of metamorphic relations U Kanewala 2014 IEEE seventh international conference on software testing, verification …, 2014 | 32 | 2014 |
Quality assurance of bioinformatics software: a case study of testing a biomedical text processing tool using metamorphic testing M Srinivasan, MP Shahri, I Kahanda, U Kanewala Proceedings of the 3rd International Workshop on Metamorphic Testing, 26-33, 2018 | 28 | 2018 |
Fault detection effectiveness of metamorphic relations developed for testing supervised classifiers P Saha, U Kanewala 2019 IEEE International conference on artificial intelligence testing …, 2019 | 26 | 2019 |
Predicting metamorphic relations for matrix calculation programs K Rahman, U Kanewala Proceedings of the 3rd International Workshop on Metamorphic Testing, 10-13, 2018 | 23 | 2018 |
Metamorphic testing for quality assurance of protein function prediction tools MP Shahri, M Srinivasan, G Reynolds, D Bimczok, I Kahanda, ... 2019 IEEE International Conference On Artificial Intelligence Testing …, 2019 | 20 | 2019 |
Experiences of testing bioinformatics programs for detecting subtle faults A Lundgren, U Kanewala Proceedings of the International Workshop on Software Engineering for …, 2016 | 17 | 2016 |
Fault detection effectiveness of source test case generation strategies for metamorphic testing P Saha, U Kanewala Proceedings of the 3rd International Workshop on Metamorphic Testing, 2-9, 2018 | 16 | 2018 |
Metamorphic testing: A simple yet effective approach for testing scientific software U Kanewala, TY Chen Computing in Science & Engineering 21 (1), 66-72, 2018 | 13 | 2018 |
Metamorphic relation prioritization for effective regression testing M Srinivasan, U Kanewala Software Testing, Verification and Reliability 32 (3), e1807, 2022 | 12 | 2022 |
Message from the workshop chairs U Kanewala, LL Pullum, S Segura, D Towey, ZQ Zhou Proceedings of the IEEE/ACM 1st International Workshop on Metamorphic …, 2016 | 11 | 2016 |
Contextual understanding and improvement of metamorphic testing in scientific software development Z Peng, U Kanewala, N Niu Proceedings of the 15th ACM/IEEE International Symposium on Empirical …, 2021 | 10 | 2021 |
MRpredT: Using text mining for metamorphic relation prediction K Rahman, I Kahanda, U Kanewala Proceedings of the IEEE/ACM 42nd International Conference on Software …, 2020 | 10 | 2020 |
Relational similarity model for suggesting friends in online social networks M Mohajireen, C Ellepola, M Perera, I Kahanda, U Kanewala 2011 6th International Conference on Industrial and Information Systems, 334-339, 2011 | 10 | 2011 |
Automated Metamorphic Testing of Scientific Software JM Bieman, A Lundgren, U Kanewala Software Engineering for Science, 185-210, 2016 | 7* | 2016 |