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Automatically analyzing groups of crashes for finding correlations.

, , , and . ESEC/SIGSOFT FSE, page 717-726. ACM, (2017)

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What makes a code change easier to review: an empirical investigation on code change reviewability., , , and . ESEC/SIGSOFT FSE, page 201-212. ACM, (2018)Why Did This Reviewed Code Crash? An Empirical Study of Mozilla Firefox., , , and . APSEC, page 396-405. IEEE, (2018)SZZ in the time of Pull Requests., , , , , , , , and . CoRR, (2022)Training convolutional neural networks for semantic classification of remote sensing imagery., , , and . JURSE, page 1-4. IEEE, (2017)Predicting the Impact of Crashes Across Release Channels., , and . CoRR, (2024)Why are Some Bugs Non-Reproducible? : -An Empirical Investigation using Data Fusion-., , and . ICSME, page 605-616. IEEE, (2020)An empirical study of patch uplift in rapid release development pipelines., , and . Empir. Softw. Eng., 24 (5): 3008-3044 (2019)An empirical study of DLL injection bugs in the Firefox ecosystem., , and . Empir. Softw. Eng., 24 (4): 1799-1822 (2019)rust-code-analysis: A Rust library to analyze and extract maintainability information from source codes., , , , , , and . SoftwareX, (2020)Why are Some Bugs Non-Reproducible? An Empirical Investigation using Data Fusion., , and . CoRR, (2021)