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Using CBR and CART to predict maintainability of relational database-driven software applications
Blekinge Institute of Technology, School of Computing.
2013 (English)Conference paper (Refereed) Published
Abstract [en]

Relational database-driven software applications have gained significant importance in modern software development. Given that software maintainability is an important quality attribute, predicting these applications' maintainability can provide various benefits to software organizations, such as adopting a defensive design and more informed resource management. Aims: The aim of this paper is to present the results from employing two well-known prediction techniques to estimate the maintainability of relational database-driven applications. Method: Case-based reasoning (CBR) and classification and regression trees (CART) were applied to data gathered on 56 software projects from software companies. The projects concerned development and/or maintenance of relational database-driven applications. Unlike previous studies, all variables (28 independent and 1 dependent) were measured on a 5-point bi-polar scale. Results: Results showed that CBR performed slightly better (at 76.8% correct predictions) in terms of prediction accuracy when compared to CART (67.8%). In addition, the two important predictors identified were documentation quality and understandability of the applications. Conclusions: The results show that CBR can be used by software companies to formalize and improve their process of maintainability prediction. Future work involves gathering more data and also employing other prediction techniques.

Place, publisher, year, edition, pages
Porto de Galinhas; Brazil: ACM , 2013.
Keyword [en]
Case-based reasoning, Classification trees, Maintainability, Prediction, Relational database-driven software applications
National Category
Software Engineering
URN: urn:nbn:se:bth-6979DOI: 10.1145/2460999.2461019Local ID: 978-145031848-8OAI: diva2:834542
17th International Conference on Evaluation and Assessment in Software Engineering, EASE
Available from: 2013-05-27 Created: 2013-05-27 Last updated: 2015-06-30Bibliographically approved

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Mendes, Emilia
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