@article {abreu2010simultaneous,
	title = {Simultaneous debugging of software faults},
	journal = {Journal of Systems and Software},
	volume = {84},
	year = {2010},
	pages = {573-586 },
	publisher = {Elsevier},
	abstract = {<p>(Semi-)automated diagnosis of software faults can drastically increase debugging efficiency, improving reliability and time-to-market. Current automatic diagnosis techniques are predominantly of a statistical nature and, despite typical defect densities, do not explicitly consider multiple faults, as also demonstrated by the popularity of the single-fault benchmark set of programs. We present a reasoning approach, called Zoltar-M(ultiple fault), that yields multiple-fault diagnoses, ranked in order of their probability. Although application of Zoltar-M to programs with many faults requires heuristics (trading-off completeness) to reduce the inherent computational complexity, theory as well as experiments on synthetic program models and multiple-fault program versions available from the software infrastructure repository (SIR) show that for multiple-fault programs this approach can outperform statistical techniques, notably spectrum-based fault localization (SFL). As a side-effect of this research, we present a new SFL variant, called Zoltar-S(ingle fault), that is optimal for single-fault programs, outperforming all other variants known to date.</p>
},
	attachments = {https://haslab.uminho.pt/sites/default/files/ruimaranhao/files/jss11.pdf},
	author = {Rui Abreu and Zoeteweij, Peter and Van Gemund, Arjan JC}
}