A Process-Driven and Ontology Based Software Product Line Variability Modeling Approach

Author(s):  
Cao Bu-Qing ◽  
Li Bing ◽  
Xia Qi-Ming
2012 ◽  
Vol 22 ◽  
pp. 134-140
Author(s):  
María Karen Cortés-Verdín ◽  
María Lucía López-Araujo ◽  
Jorge Octavio Ocharán-Hernández

Software Product Lines (SPL) take economic advantage of commonality and variability among a set of software systems that exist within a specific domain. Therefore, Software Product Line Engineering defines a series of processes for the development of a SPL that consider commonality and variability during the software life cycle. Variability modeling is therefore an essential activity in a Software Product Line Engineering approach. There are several techniques for variability modeling nowadays. COVAMOF stands out among them since it allows the modeling of variation points, variants and dependencies as first class elements. COVAMOF, therefore, provides an uniform manner for representing such concepts in different levels of abstraction within a SPL. In order to take advantage of COVAMOF benefits, it is necessary to have a computer aided tool, otherwise variability modeling and management canbe a hard tasks for the software engineer. This paper presents the development of a Eclipse plug-in for COVAMOF.


2013 ◽  
Vol 9 (1) ◽  
pp. 995-1003
Author(s):  
Cristian Martinez ◽  
Silvio Gonnet ◽  
Horacio Leone

The software product line (SPL) paradigm is used for developing software system products from a set of reusable artifacts, known as platform. The Orthogonal Variability Modeling (OVM) is a technique for representing and managing the variability and composition of those artifacts for deriving products in the SPL. Nevertheless, OVM does not support the formal analysis of the models. For example, the detection of dead artifacts (i.e., artifcats that cannot be included in any product) is an exhaustive activity which implies the verification of relationships between artifacs, artifacts parents, and so on. In this work, we introduce a Petri nets approach for representing and analyzing OVM models. The proposed net is built from elemental topologies that represents OVM concepts and relationships. Finally, we simulate the net and study their properties in order to avoid the product feasibility problems.


Author(s):  
Mahdi Bashari ◽  
Ebrahim Bagheri ◽  
Weichang Du

Runtime adaptive systems are able to dynamically transform their internal structure, and hence their behavior, in response to internal or external changes. Such transformations provide the basis for new functionalities or improvements of the non-functional properties that match operational requirements and standards. Software Product Line Engineering (SPLE) has introduced several models and mechanisms for variability modeling and management. Dynamic software product lines (DSPL) engineering exploits the knowledge acquired in SPLE to develop systems that can be context-aware, post-deployment reconfigurable, or runtime adaptive. This paper focuses on DSPL engineering approaches for developing runtime adaptive systems and proposes a framework for classifying and comparing these approaches from two distinct perspectives: adaptation properties and adaptation realization. These two perspectives are linked together by a series of guidelines that help to select a suitable adaptation realization approach based on desired adaptation types.


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.


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