Recovering software product line architecture of a family of object-oriented product variants

Abstract

International audienceSoftware Product Line Engineering (SPLE) aims at applying a pre-planned systematic reuse of large-grained software artifacts to increase the software productivity and reduce the development cost. The idea of SPLE is to analyze the business domain of a family of products to identify the common and the variable parts between the products. However, it is common for companies to develop, in an ad-hoc manner (e.g. clone and own), a set of products that share common services and differ in terms of others. Thus, many contributions are proposed to re-engineer existing product variants to a software product line. Nevertheless, these contributions are mostly focused on managing the variability at the requirement level. Few contributions address the variability at the architectural level despite its major importance. Starting from this observation, we propose an approach to reverse engineer the architecture of a set of product variants. Our goal is to identify variability and dependencies among architectural-element variants. Our work relies on formal concept analysis to analyze the variability. To validate the proposed approach, we experimented on two families of open-source product variants; Mobile Media and Health Watcher. %The results show that our approach is able to identify the architectural variability and the dependencies

Towards complex product line variability modelling: Mining relationships from non-boolean descriptions

“…An antichain is a nat if the features have no configuration in common, it does not contain a xor-group, is not included in a xor-group and, either its size is 2, or it does not contain any smaller nat. Ryssel et al [58], AL-Msie'deen et al [2] and Shatnawi et al [60] also provide algorithms to extract mutex from FCA structures. To the best of our knowledge, there is no available tool permitting to extract mutex and feature groups by means of FCA; we implemented these algorithms in our tool CLEF presented in Section 5 and available on GitHub.…”

Understanding Source Code Variability in Cloned Android Families: An Empirical Study on 75 Families

“…Figure 2 presents the numbers of Lines Of Code (LOCs) and Java files of PVs 7 to better understand the nature of the families used in our study. We have a diversity in terms of the number of PVs composing each family (2,3,4,5,6,11 PVs) and the number of LOCs and Java files of these PVs. We have families composed of PVs including very similar numbers of LOCs and Java files and families composed of PVs having varied numbers of LOCs and Java files.…”

“…These approaches aim to identify features [6] [9], software product line architectures [4] [8], reusable assets [7] [17], and feature model synthesis [18] [19] . They analyze variability between PVs based on several algorithms including FCA [4] [19], interdependent element identification [9], latent semantic indexing [6], clustering algorithm [17] and clone detection [20]. Although these approaches contribute to manage the commonality and variability of PVs by reengineering to SPLs, their aim is not to understand the commonality and variability patterns based on empirical studies on cloned android families.…”

“…Mobile applications should be in variants to follow differences in market needs and users' demands [1]. The use of the clone-and-own approach becomes a common practice used by developers to rapidly customize existing applications to meet variability in market needs [2] [3] [4].…”

“…SPLE allows us to maintain a set of PVs in parallel by managing the commonality and the variability between PVs. Indeed, many recent work have been proposed in the last years to extract SPL from cloned PVs such as [4] [6] [7] [8] [9].…”