Description
(Text)
Aspect-oriented programming (AOP) offers a new concept for improving the modularity of crosscutting concerns. The advanced composition mechanisms introduced for realizing this concept cause serious software evolution problems and prevent in particular tool-supported refactoring of aspect-oriented programs. This dissertation presents an approach to refactoring that uses change impact analysis techniques to verify the validity of behavioral compositions in aspect-oriented programs. It shows how the refactoring process can be extended to detect invalidated compositions and to adjust their specifications. In particular, the dissertation discusses and classifies general attributes of existing approaches for composing program behavior in AOP and illustrates in which way they cause evolution-related problems. It presents a model for representing the meta-level information used, which enables the detection of invalidated compositions. The presented prototype demonstrates how the proposedapproach can be integrated in mainstream refactoring tools, showing different ways to assist developers in detecting and adjusting invalidated compositions.
(Author portrait)
Jan Wloka is a postdoctoral researcher at Rutgers University, USA. He received his Ph.D. from the TU Berlin in 2007. Jan worked on integrated tool support for several years at Fraunhofer FIRST. His research on program analysis techniques targets safe change integration, refactoring for new programming models, and change-centric test development.
(Author portrait)
Wloka, Jan Jan Wloka is a postdoctoral researcher at Rutgers University, USA. He received his Ph.D. from the TU Berlin in 2007. Jan worked on integrated tool support for several years at Fraunhofer FIRST. His research on program analysis techniques targets safe change integration, refactoring for new programming models, and change-centric test development.
