Applying and Combining Three Different Aspect Mining Techniques

Understanding a software system at source-code level requires understanding the different concerns that it addresses, which in turn requires a way to identify these concerns in the source code. Whereas some concerns are explicitly represented by program entities (like classes, methods and variables) and thus are easy to identify, crosscutting concerns are not captured by a single program entity but are scattered over many program entities and are tangled with the other concerns. Because of their crosscutting nature, such crosscutting concerns are difficult to identify, and reduce the understandability of the system as a whole. In this paper, we report on a combined experiment in which we try to identify crosscutting concerns in the JHotDraw framework automatically. We first apply three independently developed aspect mining techniques to JHotDraw and evaluate and compare their results. Based on this analysis, we present three interesting combinations of these three techniques, and show how these combinations provide a more complete coverage of the detected concerns as compared to the original techniques individually. Our results are a first step towards improving the understandability of a system that contains crosscutting concerns, and can be used as a basis for refactoring the identified crosscutting concerns into aspects.Comment: 28 page

An Evaluation of Clone Detection Techniques for Identifying Crosscutting Concerns

Code implementing a crosscutting concern is often spread over many different parts of an application. Identifying such code automatically greatly improves both the maintainability and the evolvability of the application. First of all, it allows a developer to more easily find the places in the code that must be changed when the concern changes, and thus makes such changes less time consuming and less prone to errors. Second, it allows a developer to refactor the code, so that it uses modern and more advanced abstraction mechanisms, thereby restoring its modularity. In this paper, we evaluate the suitability of clone detection as a technique for the identification of crosscutting concerns. To that end, we manually identify four specific concerns in an industrial C application, and analyze to what extent clone detection is capable of finding these concerns. We consider our results as a stepping stone toward an automated "concern miner" based on clone detection

Assessing architectural evolution: A case study

This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2011 SpringerThis paper proposes to use a historical perspective on generic laws, principles, and guidelines, like Lehman’s software evolution laws and Martin’s design principles, in order to achieve a multi-faceted process and structural assessment of a system’s architectural evolution. We present a simple structural model with associated historical metrics and visualizations that could form part of an architect’s dashboard. We perform such an assessment for the Eclipse SDK, as a case study of a large, complex, and long-lived system for which sustained effective architectural evolution is paramount. The twofold aim of checking generic principles on a well-know system is, on the one hand, to see whether there are certain lessons that could be learned for best practice of architectural evolution, and on the other hand to get more insights about the applicability of such principles. We find that while the Eclipse SDK does follow several of the laws and principles, there are some deviations, and we discuss areas of architectural improvement and limitations of the assessment approach

Discovering faults in idiom-based exception handling.

ABSTRACT In this paper, we analyse the exception handling mechanism of a state-of-the-art industrial embedded software system. Like many systems implemented in classic programming languages, our subject system uses the popular return-code idiom for dealing with exceptions. Our goal is to evaluate the fault-proneness of this idiom, and we therefore present a characterisation of the idiom, a fault model accompanied by an analysis tool, and empirical data. Our findings show that the idiom is indeed fault prone, but that a simple solution can lead to significant improvements