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

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 nulls with special values, 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. Over this data set, CASPER builds a causality trace in less than 1 second.

HyperAST: Enabling Efficient Analysis of Software Histories at Scale

“…Use case #3: The third practical use case that would benefit from the HyperAST are the temporal code analyses linking and tracing code elements across history. For example, understand when a null pointer issue or a bad smell appeared in a commit [10], tracking the evolutions of a given method [15,17], measuring the stability metric of a class [41] [14,15,17], or understanding the evolution of a method complexity [28], computing change-and error-proneness of a given code element [5].…”

When traceability goes awry: An industrial experience report

“…Traceability also helps mitigate failure propagation-i.e., due to defects in the code that endure through the development cycle and potentially reach the customer (for example, see [33,34]). Aligning tests with requirements to establish coverage metrics is vital, and without this information, it can be unclear if a requirement has been correctly tested or not.…”