Facilitating the evolution of products in product line engineering by capturing and replaying configuration decisions

Software product lines rely on developing reusable artifacts and defining their variability in models to support and accelerate the derivation of individual products. A major challenge in product lines is the continuous evolution of both the reusable artifacts and derived products. Products that have been derived from a product line have to be updated regularly, e.g., after bugfixes or the development of new features. Changes to reusable artifacts and variability models have to be propagated to derived products. The aim of our research is to provide automated support for the evolution of products derived from product lines by capturing and replaying configuration decisions. Our PUPLE (Product Updates in Product Line Engineering) approach supports updating derived products after changes to the product line they have been derived from. It exploits the structure of variability models and uses change-tracking data to minimize user intervention. The paper first explores how different types of product line changes influence the derived products. It then presents extensions to our decision-oriented product line approach DOPLER to support product line evolution. We evaluate the feasibility of the PUPLE approach with evolution tasks that were performed by engineers of an industry partner on a product line of an Eclipse-based tool suite with six derived products. We conclude with lessons learned and limitations of our approach.     

A scoped approach to traceability management

Traceability is the ability to describe and follow the life of a software artifact and a means for modeling the relations between software artifacts in an explicit way. Traceability has been successfully applied in many software engineering communities and has recently been adopted to document the transition among requirements, architecture and implementation. We present an approach to customize traceability to the situation at hand. Instead of automating tracing, or representing all possible traces, we scope the traces to be maintained to the activities stakeholders must carry out. We define core traceability paths, consisting of essential traceability links required to support the activities. We illustrate the approach through two examples: product derivation in software product lines, and release planning in software process management. By using a running software product line example, we explain why the core traceability paths identified are needed when navigating from feature to structural models and from family to product level and backward between models used in software product derivation. A feasibility study in release planning carried out in an industrial setting further illustrates the use of core traceability paths during production and measures the increase in performance of the development processes supported by our approach. These examples show that our approach can be successfully used to support both product and process traceability in a pragmatic yet efficient way.     

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

ContextIn 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.ObjectiveWe aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations.MethodWe 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.ResultsWe 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.ConclusionsTools 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.     

Simulating evolution in model-based product line engineering

ContextNumerous approaches are available for modeling product lines and their variability. However, the long-term impacts of model-based development on maintenance effort and model complexity can hardly be investigated due to a lack of empirical data. Conducting empirical research in product line engineering is difficult as companies are typically reluctant to provide access to data from their product lines. Also, many benefits of product lines can be measured only in longitudinal studies, which are difficult to perform in most environments.ObjectiveIn this paper, we thus aim to explore the benefit of simulation to investigate the evolution of model-based product lines.MethodWe present a simulation approach for exploring the effects of product line evolution on model complexity and maintenance effort. Our simulation considers characteristics of product lines (e.g., size, dependencies in models) and we experiment with different evolution profiles (e.g., technical refactoring vs. placement of new products).ResultsWe apply the approach in a simulation experiment that uses data from real-world product lines from the domain of industrial automation systems to demonstrate its feasibility.ConclusionOur results demonstrate that simulation contributes to understanding the effects of maintenance and evolution in model-based product lines.     

Multi-purpose,multi-level feature modeling of large-scale industrial software systems

Feature models are frequently used to capture the knowledge about configurable software systems and product lines. However, feature modeling of large-scale systems is challenging as models are needed for diverse purposes. For instance, feature models can be used to reflect the perspectives of product management, technical solution architecture, or product configuration. Furthermore, models are required at different levels of granularity. Although numerous approaches and tools are available, it remains hard to define the purpose, scope, and granularity of feature models. This paper first reports results and experiences of an exploratory case study on developing feature models for two large-scale industrial automation software systems. We report results on the characteristics and modularity of the feature models, including metrics about model dependencies. Based on the findings from the study, we developed FORCE, a modeling language, and tool environment that extends an existing feature modeling approach to support models for different purposes and at multiple levels, including mappings to the code base. We demonstrate the expressiveness and extensibility of our approach by applying it to the well-known Pick and Place Unit example and an injection molding subsystem of an industrial product line. We further show how our approach supports consistency between different feature models. Our results and experiences show that considering the purpose and level of features is useful for modeling large-scale systems and that modeling dependencies between feature models is essential for developing a system-wide perspective.     

A novel model-based testing approach for software product lines

Model-based testing relies on a model of the system under test. FineFit is a framework for model-based testing of Java programs. In the FineFit approach, the model is expressed by a set of tables based on Parnas tables. A software product line is a family of programs (the products) with well-defined commonalities and variabilities that are developed by (re)using common artifacts. In this paper, we address the issue of using the FineFit approach to support the development of correct software product lines. We specify a software product line as a specification product line where each product is a FineFit specification of the corresponding software product. The main challenge is to concisely specify the software product line while retaining the readability of the specification of a single system. To address this, we used delta-oriented programming, a recently proposed flexible approach for implementing software product lines, and developed: (1) delta tables as a means to apply the delta-oriented programming idea to the specification of software product lines; and (2) DeltaFineFit as a novel model-based testing approach for software product lines.     

A holistic approach to feature modeling for product line requirements engineering

Requirements engineering (RE) offers the means to discover, model, and manage the requirements of the products that comprise a product line, while software product line engineering (SPLE) offers the means of realizing the products’ requirements from a common base of software assets. In practice, however, RE and SPLE have proven to be less complementary than they should. While some RE techniques, particularly goal modeling, support the exploration of alternative solutions, the appropriate solution is typically conditional on context and a large product line may have many product-defining contexts. Thus, scalability and traceability through into product line features are key challenges for RE. Feature modeling, by contrast, has been widely accepted as a way of modeling commonality and variability of products of a product line that may be very complex. In this paper, we propose a goal-driven feature modeling approach that separates a feature space in terms of problem space and solution space features, and establish explicit mappings between them. This approach contributes to reducing the inherent complexity of a mixed-view feature model, deriving key engineering drivers for developing core assets of a product line, and facilitating the quality-based product configuration.     

Structuring automotive product lines and feature models: an exploratory study at Opel

Automotive systems are highly complex and customized systems containing a vast amount of variability. Feature modeling plays a key role in customization. Empirical evidence through industry application, and in particular methodological guidance of how to structure automotive product lines and their feature models is needed. The overall aim of this work is to provide guidance to practitioners how to structure automotive product lines and their feature models, understanding strengths and weaknesses of alternative structures. The research was conducted in three phases. In the first phase, the context situation was understood using interviews and workshops. In the second phase, possible structures of product lines and feature models were evaluated based on industry feedback collected in workshops. In the third phase, the structures were implemented in the tool GEARS and practitioner feedback was collected. One key challenge was the unavailability of structuring guidelines, which was the focus of this research. The structures considered most suitable for the automotive product line were multiple product lines with modular decomposition. The structures most suitable for the feature model were functional decomposition, using context variability, models corresponding to assets, and feature categories. Other structures have been discarded, and the rationales have been presented. It was possible to support the most suitable structures with the commercial tool GEARS. The implementation in GEARS and the feedback from the practitioners provide early indications for the potential usefulness of the structures and the tool implementation.     

ZYX-a multimedia document model for reuse and adaptationof multimedia content

Advanced multimedia applications require adequate support for the modeling of multimedia content by multimedia document models. More and more this support calls for not only the adequate modeling of the temporal and spatial course of a multimedia presentation and its interactions, but also for the partial reuse of multimedia documents and adaptation to a given user context. However, our thorough investigation of existing standards for multimedia document models such as HTML, MHEG, SMIL, and HyTime leads to us the conclusion that these standard models do not provide sufficient modeling support for reuse and adaptation. Therefore, we propose a new approach for the modeling of adaptable and reusable multimedia content, the Z_YX model. The model offers primitives that provide-beyond the more or less common primitives for temporal, spatial, and interaction modeling-a variform support for reuse of structure and layout of document fragments and for the adaptation of the content and its presentation to the user context. We present the model in detail and illustrate the application and effectiveness of these concepts by samples taken from our Cardio-OP application in the domain of cardiac surgery. With the Z_YX model, we developed a comprehensive means for advanced multimedia content creation: support for template-driven authoring of multimedia content and support for flexible, dynamic composition of multimedia documents customized to the user's local context and needs. The approach significantly impacts and supports the authoring process in terms of methodology and economic aspects     

Evaluation of a traceability approach for informal freehand sketches

Most engineers and designers prefer to use large drawing boards such as whiteboards or flip charts for the initial collaborative sketching of a system’s models. Large interactive displays have recently begun to replace these physical drawing boards, blurring the line between freehand sketching and toolkit-aided modeling. While digital boards offer more flexibility in drawing and navigating models, they must also provide appropriate cognitive support for frequent shifts of focus and navigation between related artifacts. Furthermore, automated assistance in uncovering potential inconsistencies and contradictions between model sketches would be beneficial so that users do not get lost amid their sketches. In this paper, we discuss an approach to create relationships between the elements of informal hand-drawn sketches on large interactive displays by combining fuzzy search with classic information retrieval techniques. The identification and maintenance of relationships is particularly challenging because we are working with hand-drawn and hand-lettered model sketches rather than the syntactically clean models created with digital modeling toolkits. We evaluated our approach by analyzing 89 model sketches from 16 industry projects and found that it identifies relations between sketched model elements with high precision and recall.