Aspect-oriented programming (AOP) is a programming paradigm to localize and modularize the concerns that tend to be tangled and scattered across traditional programming modules, like functions or classes. Such concerns are known as crosscutting concerns and aspect-oriented languages propose to encapsulate them in modules called aspects. Because each crosscutting concern implemented in an aspect is separated from the other concerns, AOP improves reusability, readability, and maintainability of code.<p><p>While it improves separation of concerns, AOP suffers from well-known composition issues. Aspects developed in isolation may indeed interact with each other in ways that were not expected by the programmers and therefore lead to a program that does not meet its requirements. Without appropriate tools, undesired aspect interactions must be identified by reading code in order to gain global knowledge of the program and understand where and how aspects interact. Then, if the aspect language does not offer the needed support, these interactions must be resolved by invasively changing the code of the conflicting aspects to make them work together. Neither one of these solutions are acceptable since global knowledge as well as invasive and composition-specific modifications are exactly what separation of concerns seeks to avoid.<p><p>In this dissertation we show that the existing approaches to compose aspects are not entirely satisfying either with respect to separation of concerns. These approaches either rely on global knowledge and invasive modifications, which is problematic, or lack genericity and/or expressivity, which means that code reading/code modification may still be required for the aspect interactions they cannot handle.<p><p>To properly detect and resolve aspect interactions we propose a novel approach that is based on AOP itself. Since aspect composition is a concern that, by definition, crosscuts the aspects, it indeed makes sense to expect that a technique to improve the separation of crosscutting concerns such as AOP is well-suited for the task. The resulting mechanism is based on reflection principles and is called reflective AOP. <p><p>The main difference between "regular" AOP and reflective AOP lies in the parts of the system they address. While traditional AOP aims at modularizing the concerns that crosscut the base system, reflective AOP offers the possibility to handle the concerns that crosscut the aspects themselves. This is achieved by incorporating new kinds of joinpoints, pointcuts and advice into the aspect language. These new elements, which form what we call a meta joinpoint model, are dedicated to the aspect level and enable programmers to reason about and act upon the semantics of aspects at runtime. As validated on numerous examples of aspect composition, having a well-designed and principled meta joinpoint model makes it possible to deal with both the detection and the resolution of composition issues in a way that preserves the separation of concerns principle. These examples are illustrated using Phase, our prototype reflective AOP language. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished
Identifer | oai:union.ndltd.org:ulb.ac.be/oai:dipot.ulb.ac.be:2013/209849 |
Date | 07 October 2011 |
Creators | Marot, Antoine |
Contributors | Roggeman, Yves, Langerman, Stefan, Tanter, Eric, Van Der Straeten, Ragnhild, D'Hondt, Theo, Wuyts, Roel |
Publisher | Universite Libre de Bruxelles, Université libre de Bruxelles, Faculté des Sciences – Informatique, Bruxelles |
Source Sets | Université libre de Bruxelles |
Language | French |
Detected Language | English |
Type | info:eu-repo/semantics/doctoralThesis, info:ulb-repo/semantics/doctoralThesis, info:ulb-repo/semantics/openurl/vlink-dissertation |
Format | 1 v. (viii, 250 p.), No full-text files |
Page generated in 0.0019 seconds