Toward a hybrid approach to generate Software Product Line portfolios

Abstract

Software Product Line (SPL) development is a new approach to software engineering that aims at the development of a whole range of products. One of the problems which hinders the adoption of that approach is related with the management of the products of the line. Additionally, the scope of a software product line is determined by the bounds of the capabilities provided by the collection of products in the product line. This introduces new challenges related to the scope problem. One of the main three different forms of scoping is the Product Portfolio Scoping (PPS). PPS aims at defining the products that should be developed as well as their key features. While this has an impact on the actual reuse opportunities, it is usually driven from marketing aspects. Defining a product portfolio by considering costumers satisfaction and cost aspects is a NP-hard problem. This work presents a hybrid approach, which combines fuzzy inference systems and the multi-objective metaheuristics NSGA-II to support product management by generating portfolios of products, based in segments of users and the development cost of the assets of the SPL. Fuzzy inference systems are used to generate development cost of an asset by using coupling, number of code lines and cyclomatic complexity and also to estimate the quality of the products generated by the optimization module of our approach. The NSGA-II metaheuristic is used to search for products minimizing the cost and maximizing the relevance of the candidate products. The results show that the proposed approach is effective in proposing the best products in terms of relevance and cost of the assets.

Search based software engineering for software product line engineering

“…Cruz et al [36] use a hybrid approach, which combines fuzzy inference systems and the well-known multi-objective genetic algorithm, NSGAII, to help decision makers manage product lines by generating portfolios of products. These portfolios are based on user segments and the development cost of SPL products.…”

A Context-Aware Recommender System for Extended Software Product Line Configurations

“…• Inferring: use of functional metrics to a static or runtime quantifiable measurement of NFPs [9,27,29,31], which allows the detection of interactions resulting from a valid set of features. We assume that implicitly and inferring NFPs were previously specified by using state-of-the-art techniques.…”

“…We assume that implicitly and inferring NFPs were previously specified by using state-of-the-art techniques. For instance, Cruz et al [9] and Zanardini et al [31] infer NFPs based on a rigorous static source code inspection, e.g., analysis of coupling and cyclomatic complexity. In this case, the success of implicitly specifying or inferring NFPs depends very significantly on the quality of such techniques, and it also varies considerably across different systems.…”

Sip

“…Sayyad found that the combination of the PUSH and PULL methods worked well for smaller models but performed poorly when applied to the Linux kernel model. Cruz et al [Cruz et al 2013] proposed using many-objective optimisation for the generation of SPL product portfolios. For the evaluation of their work, they used the NSGA-II algorithm for the selection of products minimising cost and maximising user relevance on a library management case study with 23 features and 4 attributes per feature.…”