Casper: Debugging Null Dereferences with Dynamic Causality Traces

Benoit Cornu (1, 2) , Earl T. Barr (3) , Lionel Seinturier (2, 1) , Martin Monperrus (2, 1)

1 SPIRALS - Self-adaptation for distributed services and large software systems
2 Université de Lille, Sciences et Technologies
3 UCL - University College of London [London]

Fixing a software error requires understanding its root cause. In this paper, we introduce "causality traces", crafted execution traces augmented with the information needed to reconstruct the causal chain from the root cause of a bug to an execution error. We propose an approach and a tool, called Casper, for dynamically constructing causality traces for null dereference errors. The core idea of Casper is to inject special values, called "ghosts", into the execution stream to construct the causality trace at runtime. We evaluate our contribution by providing and assessing the causality traces of 14 real null dereference bugs collected over six large, popular open-source projects. Over this data set, Casper builds a causality trace in less than 5 seconds.

Domaines: Génie logiciel [cs.SE]

Benoit Cornu, Earl T. Barr, Lionel Seinturier, Martin Monperrus. Casper: Debugging Null Dereferences with Dynamic Causality Traces . [Research Report] hal-01113988, Inria Lille. 2015. ⟨hal-01113988v2⟩