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A Survey of Automated Code-Level Aspect Mining Techniques

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Transactions on Aspect-Oriented Software Development IV

Part of the book series: Lecture Notes in Computer Science ((TAOSD,volume 4640))

Abstract

This paper offers a first, in-breadth survey and comparison of current aspect mining tools and techniques. It focuses mainly on automated techniques that mine a program’s static or dynamic structure for candidate aspects. We present an initial comparative framework for distinguishing aspect mining techniques, and assess known techniques against this framework. The results of this assessment may serve as a roadmap to potential users of aspect mining techniques, to help them in selecting an appropriate technique. It also helps aspect mining researchers to identify remaining open research questions, possible avenues for future research, and interesting combinations of existing techniques.

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Author information

Authors and Affiliations

  1. Programming Technology Lab, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium

    Andy Kellens

  2. Département d’Ingénierie Informatique, Université catholique de Louvain, Place Sainte Barbe 2, B-1348 Louvain-la-Neuve, Belgium

    Kim Mens

  3. ITC-irst, Centro per la Ricerca Scientifica e Tecnologica, Via Sommarive 18, 38050 Trento, Italy

    Paolo Tonella

Authors
  1. Andy Kellens
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  2. Kim Mens
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  3. Paolo Tonella
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Editor information

Awais Rashid Mehmet Aksit

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© 2007 Springer-Verlag Berlin Heidelberg

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Kellens, A., Mens, K., Tonella, P. (2007). A Survey of Automated Code-Level Aspect Mining Techniques. In: Rashid, A., Aksit, M. (eds) Transactions on Aspect-Oriented Software Development IV. Lecture Notes in Computer Science, vol 4640. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77042-8_6

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  • DOI: https://doi.org/10.1007/978-3-540-77042-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77041-1

  • Online ISBN: 978-3-540-77042-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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