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Resolving model inconsistencies using automated regression planning

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Abstract

One of the main challenges in model-driven software engineering is to automate the resolution of design model inconsistencies. We propose to use the artificial intelligence technique of automated planning for the purpose of resolving such inconsistencies through the generation of one or more resolution plans. We implemented Badger, a regression planner in Prolog that generates such plans. We assess its scalability on the resolution of different types of structural inconsistencies in UML models using both generated models and reverse-engineered models of varying sizes, the largest ones containing more than 10,000 model elements. We illustrate the metamodel-independence of our approach by applying it to the resolution of code smells in a Java program. We discuss how the user can adapt the order in which resolution plans are presented by modifying the cost function of the planner algorithm.

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Notes

  1. The call predicate used as part of the can rule is a well-known Prolog meta-predicate [7].

  2. techpubs.borland.com/together/tec2006/en/readme.html.

  3. \(\bar{R}^2\) is defined as \(1-(1-R^2)\frac{n - 1}{n - p - 1}\), where \(R^2\) is the coefficient of determination, \(n\) is the sample size and \(p\) the number of parameters in the regression model.

  4. See http://c2.com/cgi/wiki?CodeSmell.

  5. findbugs.sourceforge.nets.

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Acknowledgments

This work has been partially supported by the F.R.S.–FNRS through FRFC project 2.4515.09 “Research Center on Software Adaptability”; and by research project AUWB-08/12-UMH “Model-Driven Software Evolution”, an Action de Recherche Concertée financed by the Ministère de la Communauté française - Direction générale de l’Enseignement non obligatoire et de la Recherche scientifique, Belgium.

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Authors and Affiliations

  1. Service de Génie Logiciel, Institut COMPLEXYS, Université de Mons, Place du Parc 20, 7000 , Mons, Belgium

    Jorge Pinna Puissant & Tom Mens

  2. Software Languages Lab, Vrije Universiteit Brussel, Pleinlaan 2, 1050 , Brussels, Belgium

    Ragnhild Van Der Straeten

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  1. Jorge Pinna Puissant
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  2. Ragnhild Van Der Straeten
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  3. Tom Mens
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Correspondence to Jorge Pinna Puissant.

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Communicated by Dr. Antonio Vallecillo and Dr. Juha-Pekka Tolvanen.

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Pinna Puissant, J., Van Der Straeten, R. & Mens, T. Resolving model inconsistencies using automated regression planning. Softw Syst Model 14, 461–481 (2015). https://doi.org/10.1007/s10270-013-0317-9

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