Automated Requirements Extraction and Product Configuration Verification for Software Product Line

Author(s):  
Shamim Ripon ◽  
Fahim Shahrier Rasel ◽  
Ruhul Kabir Howlader ◽  
Maheen Islam
2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Scott Uk-Jin Lee

The wide adaptation of product line engineering in software industry has enabled cost effective development of high quality software for diverse market segments. In software product line (SPL), a family of software is specified with a set of core assets representing reusable features with their variability, dependencies, and constraints. From such core assets, valid software products are configured after thoroughly analysing the represented features and their properties. However, current implementations of SPL lack effective means to configure a valid product as core assets specified in SPL, being high-dimensional data, are often too complex to analyse. This paper presents a time and cost effective methodology with associated tool supports to design a SPL model, analyse features, and configure a valid product. The proposed approach uses eXtensible Markup Language (XML) to model SPL, where an adequate schema is defined to precisely specify core assets. Furthermore, it enables automated product configuration by (i) extracting all the properties of required features from a given SPL model and calculating them with Alloy Analyzer; (ii) generating a decision model with appropriate eXtensible Stylesheet Language Transformation (XSLT) instructions embedded in each resolution effect; and (iii) processing XSLT instructions of all the selected resolution effects.


2006 ◽  
Vol 13D (1) ◽  
pp. 51-60
Author(s):  
Shin-Young Park ◽  
Soo-Dong Kim

Author(s):  
Hitesh Yadav ◽  
Rita Chhikara ◽  
Charan Kumari

Background: Software Product Line is the group of multiple software systems which share the similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organization. Objective: The objective of this research article is to obtain an optimized subset of features which are capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed. a) An improved objective function which is used to compute the contribution of each feature with weight based methodology. b) A hybrid model is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results shows that proposed hybrid model outperforms the state of art metaheuristic algorithms.


Author(s):  
SeungYong Choi ◽  
◽  
SunTae Kim ◽  
JeongAh Kim ◽  
◽  
...  

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