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Fault-Localization Using Dynamic Slicing and Change Impact Analysis
Elton Alves, Milos Gligoric, Vilas Jagannath, and Marcelo D'Amorim
(Federal University of Pernambuco, Brazil; University of Illinois at Urbana-Champaign, USA)
Spectrum-based fault-localization tools, such as Tarantula, have been developed to help guide developers towards faulty statements in a system under test. These tools report statements ranked in order of suspiciousness. Unfortunately, the reported statements can often be unrelated to the error. This paper evaluates the impact of several approaches to ignoring such unrelated statements in order to improve the effectiveness of fault-localization tools.