Enhancing Similarity Distances Using Mandatory and Optional for Early Fault Detection

Safwan Abd Razak, Mohd Adham Isa, Dayang N.A Jawawi

Abstract


Software Product Line (SPL) describes procedures, techniques, and tools in software engineering by using a common method of production for producing a group of software systems that identical from a shared set of software assets. In SPL, the similarity-based prioritization can resemble combinatorial interaction testing in scalable and efficient way by choosing and prioritize configurations that most dissimilar. However, the similarity distances in SPL still not so much cover the basic detail of feature models which are the notations. Plus, the configurations always have been prioritized based on domain knowledge but not much attention has been paid to feature model notations. In this paper, we proposed the usage of mandatory and optional notations for similarity distances. The objective is to improve the average percentage of faults detected (APFD). We investigate four different distances and make modifications on the distances to increase APFD value. These modifications are the inclusion of mandatory and optional notations with the similarity distances. The results are the APFD values for all the similarity distances including the original and modified similarity distances. Overall, the results shown that by subtracting the optional notation value can increase the APFD by 3.71% from the original similarity distance.

Keywords


Software product lines; Similarity distances algorithms; Prioritization; Average percentage of faults detected (APFD)

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DOI: http://doi.org/10.11591/ijeecs.v11.i3.pp1194-1203
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