A survey of variability modeling in industrial practice

Berger, Thorsten; Rublack, Ralf; Nair, D.; Atlee, Joanne M.; Becker, Martin; Czarnecki, Krzysztof; Wąsowski, Andrzej

doi:10.1145/2430502.2430513

Cited by 333 publications

(212 citation statements)

References 27 publications

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“…As demonstrated by the ERP example and confirmed by the literature [19,20,21,19], companies currently are employing diverse solutions for modeling variability and supporting product configuration. For the configuration of a common product in such a context, an integrative infrastructure is needed, which works on concepts shared among the different modeling notations.…”

Section: Motivating Example and Discussion Of Requirementsmentioning

confidence: 93%

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

Galindo

Dhungana

Rabiser

et al. 2015

Information and Software Technology

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Context: In industrial settings products are developed by more than one organization. Software vendors and suppliers commonly typically maintain their own product lines, which contribute to a larger (multi) product line or software ecosystem. It is unrealistic to assume that the participating organizations will agree on using a specific variability modeling technique-they will rather use different approaches and tools to manage the variability of their systems. Objective: We aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations. Method: We present an integrative approach that provides a unified perspective to users configuring products in multi product line environments, regardless of the different modeling methods and tools used internally. We also present a technical infrastructure and a prototype implementation based on web services. Results: We show the feasibility of the approach and its implementation by using it with the three most widespread types of variability modeling approaches in the product line community, i.e., feature-based, OVM-style, and decision-oriented modeling. To demonstrate the feasibility and flexibility of our approach, we present an example derived from industrial experience in enterprise resource planning. We further applied the approach to support the configuration of privacy settings in the Android ecosystem based on multiple variability models. We also evaluated the performance of different model enactment strategies used in our approach. Conclusions: Tools and techniques allowing stakeholders to handle variability in a uniform manner can considerably foster the initiation and growth of software ecosystems from the perspective of software reuse and configuration.

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Section: Motivating Example and Discussion Of Requirementsmentioning

confidence: 93%

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

Galindo

Dhungana

Rabiser

et al. 2015

Information and Software Technology

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“…We previously surveyed companies in their use of variability modeling [5] and conducted semi-structured interviews with eight of them. In the present work, we select three companies and describe and analyze them in-depth.…”

Section: -What Are the Benefits (Rq2) And What Are The Challenges (Rqmentioning

confidence: 99%

“…In the present work, we select three companies and describe and analyze them in-depth. Our selection represents a broad range of development scales from very small (two developers) to ultra-large (100 development teams); comprises domains that commonly use variability modeling (automotive, industrial applications/energy, and eCommerce [5]); and covers all product-line adoption strategies (proactive, extractive, and reactive [27]). In contrast to quantitative research, our goal is not too reach any statistically significant deductions, but to describe the practices that were successful in three heterogeneous cases.…”

Section: -What Are the Benefits (Rq2) And What Are The Challenges (Rqmentioning

confidence: 99%

“…In the present work, we strive to gain insight into how the results from the previous study relate to industrial practices. Our preceding survey [5] showed that feature models were among the most popular notations, but also that a wide range of notations and tools is used. It also confirmed the existence of large models-which have been reported before [39,38,29], but without any further characteristics, such as the use or complexity of constraints.…”

Section: Background and Related Workmentioning

confidence: 99%

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Three Cases of Feature-Based Variability Modeling in Industry

Berger

Nair

Rublack

et al. 2014

Lecture Notes in Computer Science

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Abstract. Large software product lines need to manage complex variability. A common approach is variability modeling-creating and maintaining models that abstract over the variabilities inherent in such systems. While many variability modeling techniques and notations have been proposed, little is known about industrial practices and how industry values or criticizes this class of modeling. We attempt to address this gap with an exploratory case study of three companies that apply variability modeling. Among others, our study shows that variability models are valued for their capability to organize knowledge and to achieve an overview understanding of codebases. We observe centralized model governance, pragmatic versioning, and surprisingly little constraint modeling, indicating that the effort of declaring and maintaining constraints does not always pay off.

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“…A recent survey of variability modeling showed that FMs are by far the most frequently reported notation in industry [28].…”

Section: Introductionmentioning

confidence: 99%

Composing Your Compositions of Variability Models

Acher

Combemale

Collet

et al. 2013

Lecture Notes in Computer Science

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Abstract. Modeling and managing variability is a key activity in a growing number of software engineering contexts. Support for composing variability models is arising in many engineering scenarios, for instance, when several subsystems or modeling artifacts, each coming with their own variability and possibly developed by different stakeholders, should be combined together. In this paper, we consider the problem of composing feature models (FMs), a widely used formalism for representing and reasoning about a set of variability choices. We show that several composition operators can actually be defined, depending on both matching/merging strategies and semantic properties expected in the composed FM. We present four alternative forms and their implementations. We discuss their relative trade-offs w.r.t. reasoning, customizability, traceability, composability and quality of the resulting feature diagram. We summarize these findings in a reading grid which is validated by revisiting some relevant existing works. Our contribution should assist developers in choosing and implementing the right composition operators.

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A survey of variability modeling in industrial practice

Cited by 333 publications

References 27 publications

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

Three Cases of Feature-Based Variability Modeling in Industry

Composing Your Compositions of Variability Models

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