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- Mark Harman
Facebook, London, UK
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Publication search results
found 475 matches
- 2024
- Giovani Guizzo, Jie M. Zhang, Federica Sarro, Christoph Treude, Mark Harman:
Mutation analysis for evaluating code translation. Empir. Softw. Eng. 29(1): 19 (2024) - Max Hort, Jie M. Zhang, Federica Sarro, Mark Harman:
Search-based Automatic Repair for Fairness and Accuracy in Decision-making Software. Empir. Softw. Eng. 29(1): 36 (2024) - Nadia Alshahwan, Mark Harman, Inna Harper, Alexandru Marginean, Shubho Sengupta, Eddy Wang:
Assured LLM-Based Software Engineering. CoRR abs/2402.04380 (2024) - Nadia Alshahwan, Mark Harman, Alexandru Marginean, Rotem Tal, Eddy Wang:
Observation-based unit test generation at Meta. CoRR abs/2402.06111 (2024) - Nadia Alshahwan, Jubin Chheda, Anastasia Finegenova, Beliz Gokkaya, Mark Harman, Inna Harper, Alexandru Marginean, Shubho Sengupta, Eddy Wang:
Automated Unit Test Improvement using Large Language Models at Meta. CoRR abs/2402.09171 (2024) - Nadia Alshahwan, Arianna Blasi, Kinga Bojarczuk, Andrea Ciancone, Natalija Gucevska, Mark Harman, Simon Schellaert, Inna Harper, Yue Jia, Michal Królikowski, Will Lewis, Dragos Martac, Rubmary Rojas, Kate Ustiuzhanina:
Enhancing Testing at Meta with Rich-State Simulated Populations. CoRR abs/2403.15374 (2024) - 2023
- Giovani Guizzo, Francesco Califano, Federica Sarro, Filomena Ferrucci, Mark Harman:
Inferring test models from user bug reports using multi-objective search. Empir. Softw. Eng. 28(4): 95 (2023) - Jie M. Zhang, Mark Harman, Benjamin Guedj, Earl T. Barr, John Shawe-Taylor:
Model validation using mutated training labels: An exploratory study. Neurocomputing 539: 126116 (2023) - Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Mark Harman:
A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers. ACM Trans. Softw. Eng. Methodol. 32(4): 106:1-106:30 (2023) - Angela Fan, Beliz Gokkaya, Mark Harman, Mitya Lyubarskiy, Shubho Sengupta, Shin Yoo, Jie M. Zhang:
Large Language Models for Software Engineering: Survey and Open Problems. ICSE-FoSE 2023: 31-53 - Shreshth Tuli, Kinga Bojarczuk, Natalija Gucevska, Mark Harman, Xiao-Yu Wang, Graham Wright:
Simulation-Driven Automated End-to-End Test and Oracle Inference. ICSE-SEIP 2023: 122-133 - Nadia Alshahwan, Mark Harman, Alexandru Marginean:
Software Testing Research Challenges: An Industrial Perspective. ICST 2023: 1-10 - Kaibo Liu, Yudong Han, Jie M. Zhang, Zhenpeng Chen, Federica Sarro, Mark Harman, Gang Huang, Yun Ma:
Who Judges the Judge: An Empirical Study on Online Judge Tests. ISSTA 2023: 334-346 - Milos Ojdanic, Mike Papadakis, Mark Harman:
Keeping Mutation Test Suites Consistent and Relevant with Long-Standing Mutants. ESEC/SIGSOFT FSE 2023: 2067-2071 - Shreshth Tuli, Kinga Bojarczuk, Natalija Gucevska, Mark Harman, Xiao-Yu Wang, Graham Wright:
Simulation-Driven Automated End-to-End Test and Oracle Inference. CoRR abs/2302.02374 (2023) - Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Mark Harman:
An Empirical Study on Fairness Improvement with Multiple Protected Attributes. CoRR abs/2308.01923 (2023) - Shuyin Ouyang, Jie M. Zhang, Mark Harman, Meng Wang:
LLM is Like a Box of Chocolates: the Non-determinism of ChatGPT in Code Generation. CoRR abs/2308.02828 (2023) - Ming Yan, Junjie Chen, Jie M. Zhang, Xuejie Cao, Chen Yang, Mark Harman:
COCO: Testing Code Generation Systems via Concretized Instructions. CoRR abs/2308.13319 (2023) - Yonghao Wu, Zheng Li, Jie M. Zhang, Mike Papadakis, Mark Harman, Yong Liu:
Large Language Models in Fault Localisation. CoRR abs/2308.15276 (2023) - Angela Fan, Beliz Gokkaya, Mark Harman, Mitya Lyubarskiy, Shubho Sengupta, Shin Yoo, Jie M. Zhang:
Large Language Models for Software Engineering: Survey and Open Problems. CoRR abs/2310.03533 (2023) - 2022
- Su Wang, Miran Kim, Xiaoqian Jiang, Arif Ozgun Harmanci:
Evaluation of vicinity-based hidden Markov models for genotype imputation. BMC Bioinform. 23(1): 356 (2022) - Max Hort, Maria Kechagia, Federica Sarro, Mark Harman:
A Survey of Performance Optimization for Mobile Applications. IEEE Trans. Software Eng. 48(8): 2879-2904 (2022) - Maria Kechagia, Sergey Mechtaev, Federica Sarro, Mark Harman:
Evaluating Automatic Program Repair Capabilities to Repair API Misuses. IEEE Trans. Software Eng. 48(7): 2658-2679 (2022) - Federica Sarro, Rebecca Moussa, Alessio Petrozziello, Mark Harman:
Learning From Mistakes: Machine Learning Enhanced Human Expert Effort Estimates. IEEE Trans. Software Eng. 48(6): 1868-1882 (2022) - Vali Tawosi, Federica Sarro, Alessio Petrozziello, Mark Harman:
Multi-Objective Software Effort Estimation: A Replication Study. IEEE Trans. Software Eng. 48(8): 3185-3205 (2022) - Jie M. Zhang, Mark Harman, Lei Ma, Yang Liu:
Machine Learning Testing: Survey, Landscapes and Horizons. IEEE Trans. Software Eng. 48(2): 1-36 (2022) - Baptiste Rozière, Jie Zhang, François Charton, Mark Harman, Gabriel Synnaeve, Guillaume Lample:
Leveraging Automated Unit Tests for Unsupervised Code Translation. ICLR 2022 - Mark Harman:
Scaling Genetic Improvement and Automated Program Repair. APR@ICSE 2022: 1-7 - Zeyu Sun, Jie M. Zhang, Yingfei Xiong, Mark Harman, Mike Papadakis, Lu Zhang:
Improving Machine Translation Systems via Isotopic Replacement. ICSE 2022: 1181-1192 - Maxime Cordy, Renaud Rwemalika, Adriano Franci, Mike Papadakis, Mark Harman:
FlakiMe: Laboratory-Controlled Test Flakiness Impact Assessment. ICSE 2022: 982-994
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