Sciweavers

PKDD
2010
Springer

Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs

13 years 1 months ago
Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs
Defect localisation is essential in software engineering and is an important task in domain-specific data mining. Existing techniques building on call-graph mining can localise different kinds of defects. However, these techniques focus on defects that affect the controlflow and are agnostic regarding the dataflow. In this paper, we introduce dataflowenabled call graphs that incorporate abstractions of the dataflow. Building on these graphs, we present an approach for defect localisation. The creation of the graphs and the defect localisation are essentially data mining problems, making use of discretisation, frequent subgraph mining and feature selection. We demonstrate the defect-localisation qualities of our approach with a study on defects introduced into Weka. As a result, defect localisation now works much better, and a developer has
Frank Eichinger, Klaus Krogmann, Roland Klug, Klem
Added 14 Feb 2011
Updated 14 Feb 2011
Type Journal
Year 2010
Where PKDD
Authors Frank Eichinger, Klaus Krogmann, Roland Klug, Klemens Böhm
Comments (0)