Empirical software product line engineering: A systematic literature review

Chacón-Luna, Ana Eva; Gutierrez, Antonio P.; Galindo, José; Benavides, David

doi:10.1016/j.infsof.2020.106389

Cited by 20 publications

(13 citation statements)

References 81 publications

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“…The sample of 20 case studies from 6 different domains was analyzed in detail. 7 The case studies were grouped by application domains, and the results are presented in Tables 1-8. Firstly, Table 1 lists the analyzed domains and case studies in the order in which they were selected and analyzed, providing their reference and type (i.e., academic, industry…).…”

Section: Rq1: Which Advanced Variability Modeling Characteristics And...mentioning

confidence: 99%

“…Moreover, these proposals are usually not properly integrated in Communicated by Joanne Atlee. Thus, despite the number of successful stories about the use of SPL engineering, 1 the variability and reuse management problem has not yet been solved, and both the academy and the industry continue to experiment with their own solutions and approaches [7].…”

Section: Introductionmentioning

confidence: 99%

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Empirical analysis of the tool support for software product lines

2022

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For the last ten years, software product line (SPL) tool developers have been facing the implementation of different variability requirements and the support of SPL engineering activities demanded by emergent domains. Despite systematic literature reviews identifying the main characteristics of existing tools and the SPL activities they support, these reviews do not always help to understand if such tools provide what complex variability projects demand. This paper presents an empirical research in which we evaluate the degree of maturity of existing SPL tools focusing on their support of variability modeling characteristics and SPL engineering activities required by current application domains. We first identify the characteristics and activities that are essential for the development of SPLs by analyzing a selected sample of case studies chosen from application domains with high variability. Second, we conduct an exploratory study to analyze whether the existing tools support those characteristics and activities. We conclude that, with the current tool support, it is possible to develop a basic SPL approach. But we have also found out that these tools present several limitations when dealing with complex variability requirements demanded by emergent application domains, such as non-Boolean features or large configuration spaces. Additionally, we identify the necessity for an integrated approach with appropriate tool support to completely cover all the activities and phases of SPL engineering. To mitigate this problem, we propose different road map using the existing tools to partially or entirely support SPL engineering activities, from variability modeling to product derivation.

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Section: Rq1: Which Advanced Variability Modeling Characteristics And...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Empirical analysis of the tool support for software product lines

2022

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“…The application of SLR has spread from medicine and health care into other fields. Recently, its application in some engineering fields, specifically software engineering, transportation systems, manufacturing, etc., has increased [29][30][31][32][33][34]. Later on, Kitchenham and Charters [35] modified this technique and provided a guideline to facilitate its application.…”

Section: Systematic Literature Reviewmentioning

confidence: 99%

The Resilience of Critical Infrastructure Systems: A Systematic Literature Review

et al. 2021

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Risk management is a fundamental approach to improving critical infrastructure systems’ safety against disruptive events. This approach focuses on designing robust critical infrastructure systems (CISs) that could resist disruptive events by minimizing the possible events’ probability and consequences using preventive and protective programs. However, recent disasters like COVID-19 have shown that most CISs cannot stand against all potential disruptions. Recently there is a transition from robust design to resilience design of CISs, increasing the focus on preparedness, response, and recovery. Resilient CISs withstand most of the internal and external shocks, and if they fail, they can bounce back to the operational phase as soon as possible using minimum resources. Moreover, in resilient CISs, early warning enables managers to get timely information about the proximity and development of distributions. An understanding of the concept of resilience, its influential factors, and available evaluation and analyzing tools are required to have effective resilience management. Moreover, it is important to highlight the current gaps. Technological resilience is a new concept associated with some ambiguity around its definition, its terms, and its applications. Hence, using the concept of resilience without understanding these variations may lead to ineffective pre- and post-disruption planning. A well-established systematic literature review can provide a deep understanding regarding the concept of resilience, its limitation, and applications. The aim of this paper is to conduct a systematic literature review to study the current research around technological CISs’ resilience. In the review, 192 primary studies published between 2003 and 2020 are reviewed. Based on the results, the concept of resilience has gradually found its place among researchers since 2003, and the number of related studies has grown significantly. It emerges from the review that a CIS can be considered as resilient if it has (i) the ability to imagine what to expect, (ii) the ability to protect and resist a disruption, (iii) the ability to absorb the adverse effects of disruption, (iv) the ability to adapt to new conditions and changes caused by disruption, and (v) the ability to recover the CIS’s normal performance level after a disruption. It was shown that robustness is the most frequent resilience contributing factor among the reviewed primary studies. Resilience analysis approaches can be classified into four main groups: empirical, simulation, index-based, and qualitative approaches. Simulation approaches, as dominant models, mostly study real case studies, while empirical methods, specifically those that are deterministic, are built based on many assumptions that are difficult to justify in many cases.

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“…As demonstrated in systematic literature reviews by El-Sharkawy, Yamagishi-Eichler & Schmid (2019) and Chacón-Luna et al (2020) , SPL has gained momentum lately and the interest in empirical data on SPL has increased ( Chacón-Luna et al, 2020 ). In addition to this, Software Product Lines Conference ( SPLC, 2020 ) is organized annually, regularly disseminating the progress of this research domain.…”

Section: Related Workmentioning

confidence: 99%

A product quality impacts of a mobile software product line: an empirical study

Pavlič¹,

Beranič²,

Heričko³

2021

PeerJ Computer Science

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Background The software product lines (SPL) enable development teams to fully address a systematic reuse of shared assets to deliver a family of similar software products. Mobile applications are an obvious candidate for employing an SPL approach. This paper presents our research outcomes, based on empirical data from an industry-level development project. Two development teams were confronted with the same functionalities set to be delivered through a family of native mobile applications for Android and iOS. Methods Empirical data was gathered before, during and after a year of full-time development. The data demonstrate the impact of a SPL approach by comparing the SPL and non-SPL multiple edition development. One family of products (Android apps) was developed using an SPL approach, while another (iOS apps), functionally the same, was developed without employing an SPL approach. The project generated a volume of raw and aggregated empirical data to support our research questions. Results The paper reports a positive impact of an SPL approach on product quality (internal and external) and feature output per week. As data shows, it also increases the delivery of functionalities (240% in 6 more editions), while investing the same amount of effort needed for a single-edition development. As a result of system-supported separation of development and production code, developers had a high confidence in further development. On the other hand, the second team delivered less new functionalities, only two new application editions, and lower software quality than the team that manages multi-edition development by employing an SPL approach.

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Empirical software product line engineering: A systematic literature review

Cited by 20 publications

References 81 publications

Empirical analysis of the tool support for software product lines

Empirical analysis of the tool support for software product lines

The Resilience of Critical Infrastructure Systems: A Systematic Literature Review

A product quality impacts of a mobile software product line: an empirical study

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