Towards system analysis with variability model metrics

Berger, Thorsten; Guo, Jianmei

doi:10.1145/2556624.2556641

Cited by 23 publications

(14 citation statements)

References 28 publications

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“…Model generation (a.k.a., instance generation) automatically creates instances (models) of the language, typically aiming at instances with certain properties, such as size, coverage of language concepts, or other structural characteristics (e.g., cross-tree constraints ratio [8,40,50]). Tool developers can use it to generate a set of models, useful for functional testing and performance testing of the different tools supporting the language.…”

Section: David Benavides José Galindomentioning

confidence: 99%

Usage Scenarios for a Common Feature Modeling Language

Berger

Collet

2019

Proceedings of the 23rd International Systems and Software Product Line Conference - Volume B

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Feature models are recognized as a de facto standard for variability modeling. Presented almost three decades ago, dozens of different variations and extensions to the original feature-modeling notation have been proposed, together with hundreds of variability management techniques building upon feature models. Unfortunately, despite several attempts to establish a unified language, there is still no emerging consensus on a feature-modeling language that is both intuitive and simple, but also expressive enough to cover a range of important usage scenarios. There is not even a documented and commonly agreed set of such scenarios.Following an initiative among product-line engineering researchers in September 2018, we present 14 usage scenarios together with examples and requirements detailing each scenario. The scenario descriptions are the result of a systematic process, where members of the initiative authored original descriptions, which received feedback via a survey, and which we then refined and extended based on the survey results, reviewers' comments, and our own expertise. We also report the relevance of supporting each usage scenario for the language, as perceived by the initiative's members, prioritizing each scenario. We present a roadmap to build and implement a first version of the envisaged common language. CCS CONCEPTS• Software and its engineering → Software product lines.

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Section: David Benavides José Galindomentioning

confidence: 99%

Usage Scenarios for a Common Feature Modeling Language

Berger

Collet

2019

Proceedings of the 23rd International Systems and Software Product Line Conference - Volume B

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“…In this paper we use some of those metrics for evaluating the feature model of the system, namely: number of features (NoF) [9], coefficient of conectivity-density (CoC) [4], depth of tree (DoT) [6,9], number of leaf nodes (NLeaf) [9], number of Or-feature groups [7], number of X or-feature groups [7], the ratio of variability (RoV) [4], and the theoretical (de-)selection ration (TSR) [17]. Section 4 presents interesting findings from this evaluation.…”

Section: Measures For Software Product Lines and Variability Managementmentioning

confidence: 99%

“…In this section we present an empirical evaluation of the system under a set of metrics for variability obtained from [21]. More specifically, we apply the following metrics on the feature model: number of features (NoF) [9], coefficient of connectivity-density (CoC) [4], depth of tree (DoT) [6,9], number of leaf nodes (NLeaf) [9], number of Or-feature groups [7], number of Xor-feature groups [7], the ratio of variability (RoV) [4], and the theoretical (de-)selection ration (TSR) [17]. These metrics give us information about the feature model of the system and, more importantly, about the use of the features of the system in real deployments.…”

Section: Empirical Evaluationmentioning

confidence: 99%

Applying Feature-Oriented SoftwareDevelopment in SaaS Systems: RealExperience, Measurements,and Findings

Pedreira¹,

Silva‐Coira²,

Places³

et al. 2019

JWE

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Distributing software as a service (SaaS) has become a major trend for web-based systems. However, this software distribution model poses many challenges. One of them is feature variability, that is, some features of the system may be required by some users, but not by all of them. In addition, variability is more complex than just including or excluding a feature, since different types of relationships may exist between features. The implementation of this variability, and the parametrization and configuration of the system can be complex in this context, so the development process of a SaaS system must adequately address variability management. In this paper we present an experience applying feature oriented software development (FOSD) in the context of SaaS web-based systems development. We present a real experience in the development of a web-based system for managing home care services for dependent people. The article describes the problem of variability management in this domain, and the feature model of the system. Finally, we present an empirical evaluation of the feature model of the system based on data obtained from its real deployment after two years of use. The empirical evaluation was based on state-of-the-art measures for variability management, and revealed relevant insights for software development in this context. Keywords: feature oriented software development, feature oriented domain analysis, variability management, software as a service, feature model metrics.

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“…Evaluating the maturity (or, performance) of SPLE in an organization is challenging. Various measurement techniques have been proposed, ranging from cost and decision models targeting SPLE (Ali et al 2009;Khurum et al 2008;Krüger 2016;Thummalapenta et al 2010) to metrics used to measure the product lines themselves (El-Sharkawy et al 2019;Montagud et al 2012;Berger and Guo 2014). A prominent evaluation technique for SPLE is the Family Evaluation Framework (FEF), assessing the performance of SPLE (not to be confused with the performance of the product line) in an organization along the four BAPO concerns (van der Linden et al 2004;Pohl et al 2005;.…”

Section: Introductionmentioning

confidence: 99%

Software product-line evaluation in the large

et al. 2021

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Software product-line engineering is arguably one of the most successful methods for establishing large portfolios of software variants in an application domain. However, despite the benefits, establishing a product line requires substantial upfront investments into a software platform with a proper product-line architecture, into new software-engineering processes (domain engineering and application engineering), into business strategies with commercially successful product-line visions and financial planning, as well as into re-organization of development teams. Moreover, establishing a full-fledged product line is not always possible or desired, and thus organizations often adopt product-line engineering only to an extent that deemed necessary or was possible. However, understanding the current state of adoption, namely, the maturity or performance of product-line engineering in an organization, is challenging, while being crucial to steer investments. To this end, several measurement methods have been proposed in the literature, with the most prominent one being the Family Evaluation Framework (FEF), introduced almost two decades ago. Unfortunately, applying it is not straightforward, and the benefits of using it have not been assessed so far. We present an experience report of applying the FEF to nine medium- to large-scale product lines in the avionics domain. We discuss how we tailored and executed the FEF, together with the relevant adaptations and extensions we needed to perform. Specifically, we elicited the data for the FEF assessment with 27 interviews over a period of 11 months. We discuss experiences and assess the benefits of using the FEF, aiming at helping other organizations assessing their practices for engineering their portfolios of software variants.

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Towards system analysis with variability model metrics

Cited by 23 publications

References 28 publications

Usage Scenarios for a Common Feature Modeling Language

Usage Scenarios for a Common Feature Modeling Language

Applying Feature-Oriented SoftwareDevelopment in SaaS Systems: RealExperience, Measurements,and Findings

Software product-line evaluation in the large

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