scholarly journals Towards automatic derivation of a product performance model from a UML software product line model

2008 ◽  
Author(s):  
Rasha Tawhid ◽  
Dorina C. Petriu
Keyword(s):  
Software Product Line ◽  
Product Line ◽  
Performance Model ◽  
Product Performance ◽  
Line Model ◽  
Software Product

scholarly journals Simulation-based abstractions for software product-line model checking

2012 ◽  
Author(s):  
Maxime Cordy ◽  
Andreas Classen ◽  
Gilles Perrouin ◽  
Pierre-Yves Schobbens ◽  
Patrick Heymans ◽  
...  
Keyword(s):  
Model Checking ◽  
Software Product Line ◽  
Product Line ◽  
Line Model ◽  
Simulation Based ◽  
Software Product

A Technical Assessment of Software Product Line Methodologies

2006 ◽  
Vol 13D (1) ◽  
pp. 51-60
Author(s):  
Shin-Young Park ◽  
Soo-Dong Kim
Keyword(s):  
Software Product Line ◽  
Product Line ◽  
Software Product ◽  
Technical Assessment

Hybrid Model using Firefly and BBO for Feature Selection in Software Product Line

2020 ◽  
Vol 13 ◽  
Author(s):  
Hitesh Yadav ◽  
Rita Chhikara ◽  
Charan Kumari
Keyword(s):  
Hybrid Model ◽  
High Performance ◽  
Software Product Line ◽  
Product Line ◽  
Feature Model ◽  
Software Systems ◽  
Feature Sets ◽  
Research Article ◽  
Software Product ◽  
Multiple Variants

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.

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