Last updated on Monday, October 06, 2025
@inproceedings{Laghari2016ASE,
author = {Gulsher Laghari and Alessandro Murgia and
Serge Demeyer},
booktitle = {Proceedings {ASE2016} (31st {IEEE/ACM} International
Conference on Automated Software Engineering)},
note = {Acceptance ratio: 57+14/298 = 23\%},
pages = {274-285},
publisher = {ACM},
title = {Fine-tuning spectrum based fault localisation with
frequent method item sets},
year = {2016},
abstract = {Continuous integration is a best practice adopted in
modern software development teams to identify
potential faults immediately upon project build. Once
a fault is detected it must be repaired immediately,
hence continuous integration provides an ideal
testbed for experimenting with the state of the art
in fault localisation. In this paper we propose a
variant of what is known as spectrum based fault
localisation, which leverages patterns of method
calls by means of frequent itemset mining. We compare
our variant (we refer to it as patterned spectrum
analysis) against the state of the art and
demonstrate on 351 real faults drawn from five
representative open source java projects that
patterned spectrum analysis is more effective in
localising the fault. Based on anecdotal evidence
from this comparison, we suggest avenues for further
improvements.},
annote = {internationalconference},
top = {A in CORE2014},
doi = {10.1145/2970276.2970308},
}