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Xiang Gao
Researcher at National University of Singapore
Publications - 15
Citations - 396
Xiang Gao is an academic researcher from National University of Singapore. The author has contributed to research in topics: Program synthesis & Correctness. The author has an hindex of 8, co-authored 15 publications receiving 167 citations. Previous affiliations of Xiang Gao include Shandong University & Fujitsu.
Papers
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Proceedings ArticleDOI
Fuzz testing based data augmentation to improve robustness of deep neural networks
TL;DR: This paper proposes a technique that re-purposes software testing methods, specifically mutation-based fuzzing, to augment the training data of DNNs, with the objective of enhancing their robustness, and casts the DNN data augmentation problem as an optimization problem.
Proceedings ArticleDOI
Repairing crashes in Android apps
TL;DR: The first approach to automatically repair Android apps, specifically a technique for fixing crashes in Android apps is proposed using a search-based repair framework embodied in the repair tool Droix, and evaluation of Droix on DroixBench reveals that the automatically produced patches are often syntactically identical to the human patch, and on some rare occasion even better than the humanPatch.
Proceedings ArticleDOI
Crash-avoiding program repair
TL;DR: In this article, the authors propose an integrated approach for detecting and discarding crashing patches, which fuses test and patch generation into a single process, in which patches are generated with the objective of passing existing tests, and new tests are generated to filter out over-fitted patches by distinguishing candidate patches in terms of behavior.
Journal ArticleDOI
Test-Equivalence Analysis for Automatic Patch Generation
TL;DR: This work proposes two test-Equivalence relations based on runtime values and dependencies, respectively, and presents an algorithm that performs on-the-fly partitioning of patches into test-equivalence classes.
Proceedings ArticleDOI
Binary rewriting without control flow recovery
TL;DR: E9Patch develops a suite of binary rewriting methodologies that can insert jumps to trampolines without the need to move other instructions, and is robust by design, and can scale to very large (>100MB) stripped binaries including the Google Chrome and FireFox web browsers.