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A hybrid approach to suggest software product line portfolios

dos Santos Neto, Pedro de Alcântara (författare)
Federal University of Piauí, BRA
Britto, Ricardo (författare)
Blekinge Tekniska Högskola,Institutionen för programvaruteknik
Rabêlo, Ricardo de Andrade Lira (författare)
Federal University of Piauí, BRA
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Cruz, Jonathas Jivago de Almeida (författare)
Federal University of Piauí, BRA
Lira, Lira (författare)
Federal University of Piauí, BRA
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 (creator_code:org_t)
Elsevier, 2016
2016
Engelska.
Ingår i: Applied Soft Computing. - : Elsevier. - 1568-4946 .- 1872-9681. ; 49, s. 1243-1255
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Software product line (SPL) development is a new approach to software engineering which aims at the development of a whole range of products. However, as long as SPL can be useful, there are many challenges regarding the use of that approach. One of the main problems which hinders the adoption of software product line (SPL) is the complexity regarding product management. In that context, we can remark the scoping problem. One of the existent ways to deal with scoping is the product portfolio scoping (PPS). PPS aims to define the products that should be developed as well as their key features. In general, that approach is driven by marketing aspects, like cost of the product and customer satisfaction. Defining a product portfolio by using the many different available aspects is a NP-hard problem. This work presents an improved hybrid approach to solve the feature model selection problem, aiming at supporting product portfolio scoping. The proposal is based in a hybrid approach not dependent on any particular algorithm/technology. We have evaluated the usefulness and scalability of our approach using one real SPL (ArgoUML-SPL) and synthetic SPLs. As per the evaluation results, our approach is both useful from a practitioner's perspective and scalable. © 2016 Elsevier B.V.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)

Nyckelord

Feature model selection problem
Fuzzy inference systems
NSGA-II
Product portfolio scoping
Search based feature model selection
Search based software engineering
Software product lines
Computational complexity
Computer software
Customer satisfaction
Fuzzy inference
Software design
Software engineering
Feature modeling
Scoping
Search-based software engineering
Software Product Line
Feature extraction

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