Generating a catalog of unanticipated schemas in class hierarchies using Formal Concept Analysis

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• 作者：Gabriela Aré ; valo ; Sté ; phane Ducasse ; Silvia Gordillo ; Oscar Nierstrasz
• 关键词：Object-oriented development ; Class hierarchy schemas ; Source code analysis ; Formal Concept Analysis
• 刊名：Information and Software Technology
• 出版年：2010
• 出版时间：November 2010
• 年：2010
• 卷：52
• 期：11
• 页码：1167-1187
• 全文大小：1177 K

文摘

Context

Inheritance is the cornerstone of object-oriented development, supporting conceptual modeling, subtype polymorphism and software reuse. But inheritance can be used in subtle ways that make complex systems hard to understand and extend, due to the presence of implicit dependencies in the inheritance hierarchy.

Objective

Although these dependencies often specify well-known schemas (i.e., recurrent design or coding patterns, such as hook and template methods), new unanticipated dependency schemas arise in practice, and can consequently be hard to recognize and detect. Thus, a developer making changes or extensions to an object-oriented system needs to understand these implicit contracts defined by the dependencies between a class and its subclasses, or risk that seemingly innocuous changes break them.

Method

To tackle this problem, we have developed an approach based on Formal Concept Analysis. Our Formal Concept Analysis based-Reverse Engineering methodology (FoCARE) identifies undocumented hierarchical dependencies in a hierarchy by taking into account the existing structure and behavior of classes and subclasses.

Results

We validate our approach by applying it to a large and non-trivial case study, yielding a catalog of hierarchy schemas, each one composed of a set of dependencies over methods and attributes in a class hierarchy. We show how the discovered dependency schemas can be used not only to identify good design practices, but also to expose bad smells in design, thereby helping developers in initial reengineering phases to develop a first mental model of a system. Although some of the identified schemas are already documented in existing literature, with our approach based on Formal Concept Analysis (FCA), we are also able to identify previously unidentified schemas.

Conclusions

FCA is an effective tool because it is an ideal classification mining tool to identify commonalities between software artifacts, and usually these commonalities reveal known and unknown characteristics of the software artifacts. We also show that once a catalog of useful schemas stabilizes after several runs of FoCARE, the added cost of FCA is no longer needed.