1. What are the contributions mentioned in the paper "The probabilistic program dependence graph and its application to fault diagnosis" ?
This paper presents an innovative model of a program ’ s internal behavior over a set of test inputs, called the probabilistic program dependence graph ( PPDG ), that facilitates probabilistic analysis and reasoning about uncertain program behavior, particularly that associated with faults.. This paper presents algorithms for constructing PPDGs and applying the PPDG to fault diagnosis.. This paper also presents preliminary evidence indicating that PPDGs can facilitate fault localization and fault comprehension.
read more
2. What have the authors stated for future works in "The probabilistic program dependence graph and its application to fault diagnosis" ?
The authors also presented algorithms for two applications of the PPDG: RankCP, which uses the PPDG to rank statements to assist in fault localization and FaultComp, which uses the PPDG to generate explanations to aid in fault comprehension.. In the future, the authors will base the PPDG on the interprocedural PDG, enabling the PPDG to capture the statistical dependences among program elements ( e. g., pointers and references ) whose behaviors are not confined to a single function.. The authors therefore plan to investigate the potential application of the PPDG to other software engineering tasks.. The results of the studies show the potential usefulness of the PPDG for these two software engineering tasks.
read more
