Deepak Dhungana

Supporting Product Derivation by Adapting and Augmenting Variability Models

Product derivation is the process of constructing products from the core assets in a product line. Guidance and support are needed to increase efficiency and to deal with the complexity of product derivation. Research has, however, devoted comparatively little attention to this process. In this paper we describe an approach for supporting product derivation. We show that variability models need to be prepared for concrete projects before they can be effectively utilized in the derivation process. Project-specific information and sales knowledge should be added and irrelevant variability should be pruned. We also present tool support and illustrate the approach using examples from ongoing research collaboration.

Supporting Runtime System Adaptation through Product Line Engineering and Plug-in Techniques

Product line engineering and plug-in techniques pursue different but complementary goals. Software product line engineering strives for modeling the variability of software systems on different levels of abstraction, whereas plug-in systems support software extensibility, customizability, and evolution. We present an approach demonstrating the benefits of integrating those two areas and discuss the integration of a plug-in platform for enterprise software with an existing product line engineering tool suite. The plug-in platform provides extensibility as well as runtime reconfiguration and adaptation mechanisms on the .NET platform. Automatic runtime adaptations are attained by using the knowledge documented in variability models. We discuss several usage scenarios developed in cooperation with our industry partner illustrating the need of our approach in the enterprise software domain. Finally, we validate the approach on a commercial ERP system of our industry partner.

Supporting Evolution in Model-Based Product Line Engineering

Software maintenance and evolution are among the most challenging and cost-intensive activities in software engineering. This is not different for software product lines due to their complexity and long life-span. New customer requirements, technology changes and internal enhancements lead to the continuous evolution of a product lines reusable assets. Due to the size of product lines, single stakeholders or teams can only maintain a small part of a system which poses additional challenges for evolution. This paper presents an approach supporting product line evolution by organizing variability models of large-scale product lines as a set of interrelated model fragments defining the variability of particular parts of the system. The approach allows semi-automatic merging of fragments into complete variability models. We also provide tool support to automatically detect changes that would make models and the architecture inconsistent. Furthermore, our approach supports the co-evolution of variability models and their respective meta-models. We illustrate the approach with examples from an ongoing industry collaboration.

Integrated tool support for software product line engineering

Product line engineering comprises many heterogeneous activities such as capturing the variability of reusable assets, supporting the derivation of products from the product line, evolving the product line, or tailoring the approach to the specifics of a domain. The inherent complexity of product lines implicates that tool support is inevitable to facilitate smooth performance and to avoid costly errors. Product line engineering tools have to support heterogeneous stakeholders involved in diverse activities. Tool integration therefore is of particular importance to foster their seamless cooperation. However, the integration is difficult to achieve due to the diversity of models and work products. This paper describes the DOPLER tool suite which has been developed to provide such integrated support. The tool suite is flexible and extensible to support domain-specific needs

Integrated Support for Product Configuration and Requirements Engineering in Product Derivation

Deriving a product from a product line means selecting and configuring existing reusable assets to meet a particular customers needs. The blue-sky scenario in product derivation is that all customer requirements can be satisfied by exploiting existing assets and their variability. The more realistic scenario, however, is that the customers will have additional wishes and requirements that are not covered by the product line. We therefore need integrated support for both product configuration and requirements engineering tasks. New requirements captured during the sales process need to be related to existing assets. In this paper we present a tool-supported approach for integrated product configuration and requirements engineering. We illustrate the approach using a scenario developed in our research collaboration with a leading company in the steel plant building domain.

Model-Based Customization and Deployment of Eclipse-Based Tools: Industrial Experiences

Developers of software engineering tools are facing high expectations regarding capabilities and usability. Users expect tools tailored to their specific needs and integrated in their working environment. This increases tools complexity and complicates their customization and deployment despite available mechanisms for adaptability and extensibility. A main challenge lies in understanding and managing the dependencies between different technical mechanisms for realizing tool variability. We report on industrial experiences of applying a model-based and tool-supported product line approach for the customization and deployment of two Eclipse-based tools. We illustrate challenges of customizing these tools to different development contexts: In the first case study we developed variability models of a product line tool suite used by an industry partner and utilized these models for tool customization and deployment. In the second case study we applied the same approach to a maintenance and setup tool of our industry partner. Our experiences suggest to design software tools as product lines; to formally describe the tools variability in models; and to provide end-user capabilities for customizing and deploying the tools.

Decision-Oriented Modeling of Product Line Architectures

Understanding and modeling architectural variability is fundamental in product line engineering. Various extensions have been proposed to architecture description languages (ADLs) to deal with variability. Although these extensions are useful, we argue in this paper that decisions need to be treated as first-class citizens for modeling architectural variability. Decisions that have to be taken by different stakeholders during product derivation are an essential source to understand the variability at different levels (e.g., features, architecture, and implementation). We outline a decision-oriented approach to variability modeling and illustrate it with an example from our ongoing research collaboration with Siemens VAI.

Architectural Knowledge in Product Line Engineering: An Industrial Case Stu

Capturing and sharing architectural knowledge is already a complex endeavor when dealing with conventional software systems for single customers. In product line engineering, however, the situation is even more difficult due to architectural variability and complex relationships between features and technical solution components. In this paper, we present our experiences and approaches taken in eliciting and sharing architectural knowledge for the software product line infrastructure of a company in the plant building domain. An important lesson learned is the necessity of capturing architectural knowledge and making this knowledge available appropriately to various stakeholders in the product line environment

A component plug-in architecture for the .NET platform

Plug-in architectures and platforms represent a promising approach for building software systems which are extensible and customizable to the particular needs of the individual user. For example, the Eclipse platform, as the most prominent representative of plug-in systems, is based on a unique plug-in and extensibility concept and has succeeded in establishing itself as the leading platform for the development of tool environments. This paper introduces a new plug-in architecture for the .NET platform which shows much resemblance to Eclipse. However, whereas Eclipse is a Java-based system and uses XML to describe extensions, our architecture relies on .NET concepts such as custom attributes and metadata to specify relevant information directly in the source code of an application. We argue that this approach is more readable and easier to maintain. As a case study for our plug-in architecture we present a new plug-in platform for implementation of rich client applications in .NET.

Managing the Life-cycle of Industrial Automation Systems with Product Line Variability Models

The current trend towards component-based software architectures has also influenced the development of industrial automation systems (IAS). Despite many advances, the life-cycle management of large-scale, component-based IAS still remains a big challenge. The knowledge required for the maintenance and runtime reconfiguration is often tacit and relies on individual stakeholders capabilities - an error-prone and risky strategy in safety critical environments. This paper presents an approach based on product line variability models to manage the lifecycle of IAS and to automate the maintenance and reconfiguration process. We complement the standard IEC 61499 with a variability modeling approach to support both initial deployment and runtime reconfiguration. We illustrate the automated model-based life-cycle management and maintenance process using sample IAS usage scenarios.