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• W4308641610 abstract "Fault Localization (FL) is a precursor step to most Automated Program Repair (APR) approaches, which fix the faulty statements identified by the FL tools. We present FixLocator, a Deep Learning (DL)-based fault localization approach supporting the detection of faulty statements in one or multiple methods that need to be modified accordingly in the same fix. Let us call them co-change (CC) fixing locations for a fault. We treat this FL problem as dual-task learning with two models. The method-level FL model, MethFL, learns the methods to be fixed together. The statement-level FL model, StmtFL, learns the statements to be co-fixed. Correct learning in one model can benefit the other and vice versa. Thus, we simultaneously train them with soft-sharing the models' parameters via cross-stitch units to enable the propagation of the impact of MethFL and StmtFL onto each other. Moreover, we explore a novel feature for FL: the co-changed statements. We also use Graph-based Convolution Network to integrate different types of program dependencies." @default.
• W4308641610 created "2022-11-13" @default.
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• W4308641610 date "2022-11-07" @default.
• W4308641610 modified "2023-09-27" @default.
• W4308641610 title "Fault localization to detect co-change fixing locations" @default.
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• W4308641610 doi "https://doi.org/10.1145/3540250.3549137" @default.
• W4308641610 hasPublicationYear "2022" @default.
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