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Once a failure is observed, the primary concern of the developer is toidentify what caused it in order to repair the code that induced the incorrectbehavior. Until a permanent repair is afforded, code repair patches areinvaluable. The aim of this work is to devise an automated patch generationtechnique that proceeds as follows: Step1) It identifies a set offailure-causing control dependence chains that are minimal in terms of numberand length. Step2) It identifies a set of predicates within the chains alongwith associated execution instances, such that negating the predicates at thegiven instances would exhibit correct behavior. Step3) For each candidatepredicate, it creates a classifier that dictates when the predicate should benegated to yield correct program behavior. Step4) Prior to each candidatepredicate, the faulty program is injected with a call to its correspondingclassifier passing it the program state and getting a return value predictivelyindicating whether to negate the predicate or not. The role of the classifiersis to ensure that: 1) the predicates are not negated during passing runs; and2) the predicates are negated at the appropriate instances within failing runs.We implemented our patch generation approach for the Java platform andevaluated our toolset using 148 defects from the Introclass and Siemensbenchmarks. The toolset identified 56 full patches and another 46 partialpatches, and the classification accuracy averaged 84%.

ACDC: Altering Control Dependence Chains for Automated Patch Generation