221 research outputs found

    Toward automated refactoring of crosscutting concerns into aspects

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    Aspect-oriented programing (AOP) improves the separation of concerns by encapsulating crosscutting concerns into aspects. Thus, aspect-oriented programing aims to better support the evolution of systems. Along this line, we have defined a process that assists the developer to refactor an object-oriented system into an aspect-oriented one. In this paper we propose the use of association rules and Markov models to improve the assistance in accomplishing some of the tasks of this process. Specifically, we use these techniques to help the developer in the task of encapsulating a fragment of aspectizable code into an aspect. This includes the choice of a fragment of aspectizable code to be encapsulated, the selection of a suitable aspect refactoring, and the analysis and application of additional restructurings when necessary. Our case study of the refactoring of a J2EE system shows that the use of the process reduces the intervention of the developer during the refactoring.Fil: Vidal, Santiago Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Marcos, Claudia Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentin

    Aspect-oriented refactoring of Java programs

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    An evaluation of clone detection techniques for identifying crosscutting concerns

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    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

    Isolating crosscutting concerns in system software

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    This paper reports upon our experience in automatically migrating the crosscutting concerns of a large-scale software system, written in C, to an aspect-oriented implementation. We zoom in on one particular crosscutting concern, and show how detailed information about it is extracted from the source code, and how this information enables us to characterise this code and define an appropriate aspect automatically. Additionally, we compare the already existing solution to the aspect-oriented solution, and discuss advantages as well as disadvantages of both in terms of selected quality attributes. Our results show that automated migration is feasible, and can lead to significant improvements in source code qualit

    Metrics for Aspect Mining Visualization

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    Aspect oriented programming has over the last decade become the subject of intense research within the domain of software engineering. Aspect mining, which is concerned with identification of cross cutting concerns in legacy software, is an important part of this domain. Aspect refactoring takes the identified cross cutting concerns and converts these into new software constructs called aspects. Software that have been transformed using this process becomes more modularized and easier to comprehend and maintain. The first attempts at mining for aspects were dominated by manual searching and parsing through source code using simple tools. More sophisticated techniques have since emerged including evaluation of execution traces, code clone detection, program slicing, dynamic analysis, and use of various clustering techniques. The focus of most studies has been to maximize aspect mining performance measured by various metrics including those of aspect mining precision and recall. Other metrics have been developed and used to compare the various aspect mining techniques with each other. Aspect mining automation and presentation of aspect mining results has received less attention. Automation of aspect mining and presentation of results conducive to aspect refactoring is important if this research is going to be helpful to software developers. This research showed that aspect mining can be automated. A tool was developed which performed automated aspect mining and visualization of identified cross cutting concerns. This research took a different approach to aspect mining than most aspect mining research by recognizing that many different categories of cross cutting concerns exist and by taking this into account in the mining process. Many different aspect mining techniques have been developed over time, some of which are complementary. This study was different than most aspect mining research in that multiple complementary aspect mining algorithms was used in the aspect mining and visualization process

    Applying and Combining Three Different Aspect Mining Techniques

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    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

    Guest Editorial: Special Issue on Software, Maintenance and Evolution

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    Software maintenance and evolution continues to play a vital role in the development of software systems. It is widely acknowledged that the majority of development effort, and thereby expenditure, is allocated to postinitial release activity. This activity, which takes place after the software has seen its first release, is known as software maintenance (or software evolution)
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