Last updated on Monday, October 06, 2025
@inproceedings{Laghari2018SACSVT,
author = {Gulsher Laghari and Serge Demeyer},
booktitle = {Proceedings {SAC-SVT 2018} (Software Verification and
Testing at the 33rd {ACM/SIGAPP} Symposium on Applied
Computing)},
note = {Acceptance ratio: 11 / 43 = 25\%},
publisher = {ACM},
title = {On the Use of Sequence Mining within Spectrum Based
Fault Localisation},
year = {2018},
abstract = {Spectrum based fault localisation is a widely studied
class of heuristics for locating faults within a
software program. Unfortunately, the current state of
the art ignores the inherent dependencies between the
methods leading up to the fault, hence having a
limited diagnostic accuracy. In this paper we present
a variant of spectrum based fault localisation, which
leverages series of method calls by means of sequence
mining. We validate our variant (we refer to it as
sequenced spectrum analysis) on the Defects4J
benchmark, demonstrating that sequenced spectrum
analysis gains a 12\% points improvement against the
state of the art.},
annote = {internationalconference},
doi = {10.1145/3167132.3167337},
}