Amine Mohamed Rouane Hacene

Refactorings of design defects using relational concept analysis

Software engineers often need to identify and correct design defects, i.e., recurring design problems that hinder development and maintenance by making programs harder to comprehend and/or evolve. While detection of design defects is an actively researched area, their correction- mainly a manual and time-consuming activity- is yet to be extensively investigated for automation. In this paper, we propose an automated approach for suggesting defect-correcting refactorings using relational concept analysis (RCA). The added value of rca consists in exploiting the links between formal objects which abound in a software re-engineering context. We validated our approach on instances of the Blob design defect taken from four different open-source programs.

Soundness and Completeness of Relational Concept Analysis

Relational Concept Analysis (RCA) is an extension of Formal Concept Analysis (FCA) to the processing of relational datasets, i.e., made of (objects X properties) contexts and (objects X objects) relations. RCA constructs a set of fixpoint concept lattices by iteratively expanding the lattices of the initial contexts. To that end, at each iteration a scaling mechanism translates the inter-object links into relational attributes that reflect the available conceptual structures. The output of a RCA task has so far only been described operationally. We propose here an analytic characterization thereof, i.e., a completeness and consistence result connecting fixpoint extents to particular relational structures in the input data.