Exploring software engineering data with formal concept analysis

Given the software engineering (SE) data, there does exist the binary relationship between entities and their properties within the data. Users are usually interested in their meaningful groupings of entities and properties. Formal concept analysis (FCA) is a powerful technique to deal with the binary relation between entities and entity properties to infer a hierarchy of concepts. The output of FCA is the concept lattice, where higher-level concepts represent general properties shared by many entities, while lower-level concepts represent the entity-specific properties. FCA has been widely and successfully used as a useful data analysis technique in various SE field, such as software comprehension, change impact analysis, refactoring, fault localization, and etc.