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Selforganizology, 2016, 3(2): 59-74
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Article

Automated inconsistency detection in feature models: A generative programming based approach

Muhammad Javed1, Muhammad Naeem2, Aarif Iqbal Umar1, Faisal Bahadur1
1Department of Information Technology, Hazara University, Mansehra, Pakistan
2Department of Information Technology, Abbottabad University of Science and Technology, Havelian, Pakistan

Received 5 March 2016;Accepted 10 April 2016;Published online 1 June 2016
IAEES

Abstract
The quality of feature model represents the quality of end products because it is used to develop products. Hence, quality evaluation of feature model is the most important task. The quality detection mechanism should be efficient enough to evaluate the quality of a given feature model within limited time. So, there is a need of automated quality evaluation system. Generative Programming (GP) is the most effective way to automate the quality detection system for feature models. This effort is to present an efficient way to automate the quality detection system by using one of the GP based technique (GenVoca Layered Architecture) for inconsistencies in feature model. We implemented this quality detection technique in C++. We applied this technique on the feature models contain errors.

Keywords quality of feature models;maturity model;Generative Programming (GP);inconsistencies;GenVoca Layered Architecture.


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