Visual Tool Support for Configuring and Understanding Software Product Lines

Botterweck, Goetz; Thiel, Steffen; Nestor, Daren; Abid, Saad bin; Cawley, Ciarán

doi:10.1109/splc.2008.32

Cited by 36 publications

(33 citation statements)

References 20 publications

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“…For instance, making a decision might cause several features to become selected, which in turn require a number of components to be implemented. The details of this meta-model are out of scope for this paper and the interested reader is guided to a previous publication [19] for further information.…”

Section: Meta-modelmentioning

confidence: 99%

A Discussion of Three Visualisation Approaches to Providing Cognitive Support in Variability Management

Cawley¹,

Healy²,

Botterweck³

2010

Software-Technologien Und -Prozesse

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Variability management in software intensive systems can be a complex and cognitively challenging process. Configuring a Software Product Line with thousands of variation points in order to derive a specific product variant is an example of such a challenge. Each configurable feature can have numerous relationships with many other elements within the system. These relationships can impact greatly on the overall configuration process. Understanding the nature and impact of these relationships during configuration is key to the quality and efficiency of the configuration process. In this paper we present an overview of three visual approaches to this configuration which utilise information visualisation techniques and aspects of cognitive theory to provide stakeholder support. Using an industry example, we discuss and compare the approaches using a set of fundamental configuration tasks.

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Section: Meta-modelmentioning

confidence: 99%

A Discussion of Three Visualisation Approaches to Providing Cognitive Support in Variability Management

Cawley¹,

Healy²,

Botterweck³

2010

Software-Technologien Und -Prozesse

Self Cite

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“…Many SPL research approaches (Czarnecki et al, 2004) focus on single development artefacts. In order to exploit real benefits of a product line we need to connect these isolated models (Botterweck et al, 2008). The authors have identified potential PD tasks in a form of scenarios.…”

Section: Product Derivation Tasksmentioning

confidence: 99%

“…The authors have identified potential PD tasks in a form of scenarios. The scenarios are illustrated with a sample product line (RESCU product line (Botterweck et al, 2008)). Decision, Feature and Component models are modeled artefacts from the RESCU product line for automotive restraint systems.…”

Section: Product Derivation Tasksmentioning

confidence: 99%

Resolving Traceability Issues in Product Derivation for Software Product Lines

Abid¹

2009

Proceedings of the 4th International Conference on Software and Data Technologies

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Abstract:Dealing with traceability management issues during model based product derivation in large complex industrial SPL is error prone due to the lack of tool support. As a result traceability management between connected models emerges as an important research topic. In this position paper, we discuss research challenges as scenarios from developed example product line and give recommendations on resolving traceability issues during product derivation. We also discuss initial ideas about our proposed approach for resolving traceability issues for efficient change management. It is foreseen that the proposed traceability management recommendations will help to understand the traceability issues during product derivation and as a result of implementing them will help us to get a bit closer to our ultimate goal of, 1) efficiently automate the product derivation, 2) reduce the production cost, 3) improve productivity and 4) improve change management in SPL.

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“…Feature models are information models that describe a set of possible products presented in a single coherent model [3], [4]. Because of the increased demand for software products, variability models tend to grow very large in size (comprising thousands of features in several cases) and increase in complexity due to the myriad of relationships that could exist among the features in the model, making it a challenge and error-prone to handle, manage and visualise these large-scale models using current existing approaches [5], [6], [7], [8]. However, in a real-life context, feature relationships can emerge in a number of ways.…”

Section: Introductionmentioning

confidence: 99%

MUSA: A Scalable Multi-touch and Multi-perspective Variability Management Tool

Garba

Noureddine

Bashroush

2016

2016 13th Working IEEE/IFIP Conference on Software Architecture (WICSA)

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Abstract-Variability management is one of the main activities in the Software Product Line Engineering process. Common and varied features of related products are modelled along with the dependencies and relationships among them. With the increase in size and complexity of product lines and the more holistic systems approach to the design process, managing the evergrowing variability models has become a challenge. In this paper, we present MUSA, a tool for managing variability and features in large-scale models. MUSA adopts the Separation of Concerns design principle by providing multiple perspectives to the model, each conveying different set of information. The demonstration is conducted using a real-life model (comprising of 1000+ features) particularly showing the Structural View, which is displayed using a mind-mapping visualisation technique (hyperbolic trees), and the Dependency View, which is displayed graphically using logic gates.

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Visual Tool Support for Configuring and Understanding Software Product Lines

Abstract: Abstract

Cited by 36 publications

References 20 publications

A Discussion of Three Visualisation Approaches to Providing Cognitive Support in Variability Management

A Discussion of Three Visualisation Approaches to Providing Cognitive Support in Variability Management

Resolving Traceability Issues in Product Derivation for Software Product Lines

MUSA: A Scalable Multi-touch and Multi-perspective Variability Management Tool

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