Improving Effectiveness in the Identification of Crosscutting Concerns in Source Code

Although aspect mining techniques are supposed to help software developers in discovering where crosscutting concerns are located in source code, in practice, the amount of user involvement required hinder their applicability. The large number of yielded candidates in conjunction with the exhibition...

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Autores principales: Abait, Esteban S., Marcos, Claudia A.
Formato: Objeto de conferencia Resumen
Lenguaje:Inglés
Publicado: 2010
Materias:
Ciencias Informáticas
aspect mining
decision making
crosscutting concerns
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/153051
http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-asse-32.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
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record_format dspace
spelling I19-R120-10915-1530512023-05-16T20:04:10Z http://sedici.unlp.edu.ar/handle/10915/153051 http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-asse-32.pdf issn:1850-2792 Improving Effectiveness in the Identification of Crosscutting Concerns in Source Code Abait, Esteban S. Marcos, Claudia A. 2010 2010 2023-05-16T13:21:47Z en Ciencias Informáticas aspect mining decision making crosscutting concerns Although aspect mining techniques are supposed to help software developers in discovering where crosscutting concerns are located in source code, in practice, the amount of user involvement required hinder their applicability. The large number of yielded candidates in conjunction with the exhibition of low precision and low recall constitutes the main pitfalls that current aspect mining techniques suffer from. In order to overcome the aforementioned problems we propose to restate the aspect mining problem as a decision making problem. If each aspect mining technique is considered to be an expert on its own, the combination of multiple expert judgments is supposed to improve the effectiveness of the identification process. The proposed approach uses several aspect mining algorithms whose results are combined using a technique known as linear opinion pool. A linear opinion pool is a mathematical combination method commonly used in decision making for aggregating the opinions of several experts in a given area. The output of the proposed approach is a ranking of source code elements (candidate seeds) that may correspond to a crosscutting concern. Our main hypothesis are: (1) the application of decision making techniques reduces the number of generated candidate seeds while improving the precision, and (2) by combining techniques based on different program analysis techniques (as static analysis or dynamic analysis) the recall can be improved. Preliminary results shows the viability of the approach and the validity of our claims. Sociedad Argentina de Informática e Investigación Operativa Objeto de conferencia Resumen http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 612-612
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
aspect mining
decision making
crosscutting concerns
spellingShingle Ciencias Informáticas
aspect mining
decision making
crosscutting concerns
Abait, Esteban S.
Marcos, Claudia A.
Improving Effectiveness in the Identification of Crosscutting Concerns in Source Code
topic_facet Ciencias Informáticas
aspect mining
decision making
crosscutting concerns
description Although aspect mining techniques are supposed to help software developers in discovering where crosscutting concerns are located in source code, in practice, the amount of user involvement required hinder their applicability. The large number of yielded candidates in conjunction with the exhibition of low precision and low recall constitutes the main pitfalls that current aspect mining techniques suffer from. In order to overcome the aforementioned problems we propose to restate the aspect mining problem as a decision making problem. If each aspect mining technique is considered to be an expert on its own, the combination of multiple expert judgments is supposed to improve the effectiveness of the identification process. The proposed approach uses several aspect mining algorithms whose results are combined using a technique known as linear opinion pool. A linear opinion pool is a mathematical combination method commonly used in decision making for aggregating the opinions of several experts in a given area. The output of the proposed approach is a ranking of source code elements (candidate seeds) that may correspond to a crosscutting concern. Our main hypothesis are: (1) the application of decision making techniques reduces the number of generated candidate seeds while improving the precision, and (2) by combining techniques based on different program analysis techniques (as static analysis or dynamic analysis) the recall can be improved. Preliminary results shows the viability of the approach and the validity of our claims.
format Objeto de conferencia
Resumen
author Abait, Esteban S.
Marcos, Claudia A.
author_facet Abait, Esteban S.
Marcos, Claudia A.
author_sort Abait, Esteban S.
title Improving Effectiveness in the Identification of Crosscutting Concerns in Source Code
title_short Improving Effectiveness in the Identification of Crosscutting Concerns in Source Code
title_full Improving Effectiveness in the Identification of Crosscutting Concerns in Source Code
title_fullStr Improving Effectiveness in the Identification of Crosscutting Concerns in Source Code
title_full_unstemmed Improving Effectiveness in the Identification of Crosscutting Concerns in Source Code
title_sort improving effectiveness in the identification of crosscutting concerns in source code
publishDate 2010
url http://sedici.unlp.edu.ar/handle/10915/153051
http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-asse-32.pdf
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