Feature location in a collection of software product variants using formal concept analysis

Using equivalence relations de- fined for each single column, we are able to translate the bicluster mining problem in terms of the partition pattern structure framework.. We show

Our approach attempts to find evidence of the relations to be evaluated in a reference corpus (associated to the same domain of the ontology) using formal concept analysis.. To

To assist a human expert to document the mined feature implementations, we propose an automatic approach which associates names and descriptions using source code ele- ments of

Many different case studies have been used for evaluating feature location in software families [5]. For instance, ArgoUML variants [8] have been exten- sively used. However, none

Friendly for customizable benchmark generation: The fact that Eclipse releases contain few variants can be seen as a limitation for benchmarking in other desired scenarios with

For reliability analysis, one can choose two product-line analysis strategies [72]: (1) bind vari- ability in a PMC deriving a variability-free model (i.e., DTMC) for each

1.1 Formal Concept Analysis for Interactive Query Refinement Formal Concept Analysis (FCA) has been used in corpus-based information retrieval for the construction and

EFLBench is aimed to be used with any set of Eclipse variants including vari- ants with features that are not part of any official release. Figure 5 illustrates, at the top, the