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Title |
A Novel Approach for Feature Selection Support of a Software Product Line Development |
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Author |
Pujianto Yugopuspito, Made Murwantara, Adrian Hartanto Sutomo |
| Citation |
Vol. 12 No. 6 pp. 107-115 |
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Abstract |
Features selection of a feature model is the key point of a Software Product Line development. It selects the most suitable configuration of features that will be included into a Software Product Line, based on the user requirements. However, features of a feature model may comprise dependency and multi functionality that correspond to the quality attributes, where it will pin points the specific product. Further, features may also have constraints to their relationship, which will influence the whole elements of product configuration. To this, we proposed an approach that utilizes the hybrid Analytic Network Process (ANP). In our proposed approach, first, the groups of features functionality are grouped to identify the non-functional factor. Then, the non-functional factors are grouped in a network for a specific quality attribute. Subsequently, the networks of specific quality attributes are merged to have global view of quality attribute dependency. At the end, the dependency for each group of quality attributes is calculated using AHP and ANP. The final result is composition guidance for product line configuration. In this paper, we use an eLearning Product Line (eLPL) case study to demonstrate the feasibility of our approach. |
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Keywords |
Software Product Line Engineering, Feature, Feature Model, Analytical Network Process, Analytical Hierarchy Process |
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