Work

Casper: Automatic tracking of null dereferences to inception with causality traces

Year: 2016

Type: article

Abstract: 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 , based on code transformation, which dynamically constructs causality traces for null dereference errors. The core idea of Casper is to replace null s with special objects, called “ghosts”, that track the propagation of the nulls from inception to their error-triggering dereference. Causality traces are extracted from these ghosts. 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.

Source: Journal of Systems and Software

DOI: 10.1016/j.jss.2016.08.062

Authors: Benoit Cornu, Earl T. Barr, Lionel Seinturier, Martin Monperrus

Institutions: Université de Lille, Centre de Recherche en Informatique, Signal et Automatique de Lille, University College London

Language: English

Topic: Software Testing and Debugging Techniques

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,820

Funder: Engineering and Physical Sciences Research Council