Christian Kröher

EASy-producer: product line development for variant-rich ecosystems

Development of software product lines requires tool support, e.g., to define variability models, to check variability models for consistency and to derive the artifacts for a specific product. Further capabilities are required when product lines are combined to software ecosystems, i.e., management and development of distributed product lines across multiple different organizations. In this paper, we describe EASy-Producer, a prototypical tool set for the development of software product lines in general and variant-rich ecosystems in particular. To support the product line engineer, EASy-Producer differentiates between simplified views limiting the capabilities and expert views unleashing its full power. We will discuss how these two views support the definition of variability models, the derivation of product configurations and the instantiation of artifacts.

Supporting heterogeneous compositional multi software product lines

Software Product Line Engineering is inherently complex. This complexity increases further if multiple product line infrastructures are composed to yield the final products, an approach sometimes referred to as Multi Software Product Lines (MSPL). In this paper, we present an approach that targets this development scenario. The approach we present here aims at a lightweight, scalable, and practical approach to variability management for multi software product lines. Our approach explicitly supports heterogeneous product lines, i.e. situations where the various product lines use different generation approaches. The approach has been implemented in the EASy-Producer tool set and applied on some case studies.

An Analysis of Variability Modeling Concepts: Expressiveness vs. Analyzability

Variability modeling is a core activity of software product line engineering. Over the years, many different approaches to variability modeling have been proposed. Typically, the individual approaches have been designed without a detailed justification on why certain modeling concepts should be used. This yields a rather unfunded selection of modeling approaches in practice, e.g., selecting approaches that provide higher modeling concepts than actually needed, but less analyses capabilities than required. Thus, we propose that the focus of an analysis should not be to determine the best modeling language, but rather to provide a characterization on when to use what kind of approach. In particular, the selection of one approach for a specific situation should be driven from the required modeling concepts (expressiveness) and the required analyzability.

Variability in service-oriented systems: an analysis of existing approaches

In service-oriented systems services can be easily reused and shared without modification. However, there are business situations where a variation of services is needed to meet the requirements of a specific customer or context. Variation of software systems has been well researched in product line engineering in terms of Variability Implementation Techniques (VITs). While most VITs focus on the customization of traditional software systems, several VITs have been developed for service-oriented systems. In this paper, we discuss the problem of service customization and provide an overview of different VITs for service variability. For this purpose, we will define four dimensions to describe, characterize and analyze existing VITs: the technical core idea, the object of variation, the forms of variation, and the binding time.

KernelHaven: an experimentation workbench for analyzing software product lines

Systematic exploration of hypotheses is a major part of any empirical research. In software engineering, we often produce unique tools for experiments and evaluate them independently on different data sets. In this paper, we present KernelHaven as an experimentation workbench supporting a significant number of experiments in the domain of static product line analysis and verification. It addresses the need for extracting information from a variety of artifacts in this domain by means of an open plug-in infrastructure. Available plug-ins encapsulate existing tools, which can now be combined efficiently to yield new analyses. As an experimentation workbench, it provides configuration-based definitions of experiments, their documentation, and technical services, like parallelization and caching. Hence, researchers can abstract from technical details and focus on the algorithmic core of their research problem. KernelHaven supports different types of analyses, like correctness checks, metrics, etc., in its specific domain. The concepts presented in this paper can also be transferred to support researchers of other software engineering domains. The infrastructure is available under Apache 2.0: https://github.com/KernelHaven. The plug-ins are available under their individual licenses.

KernelHaven: an open infrastructure for product line analysis

KernelHaven is an open infrastructure for Software Product Line (SPL) analysis. It is intended both as a production-quality analysis tool set as well as a research support tool, e.g., to support researchers in systematically exploring research hypothesis. For flexibility and ease of experimentation KernelHaven components are plug-ins for extracting certain information from SPL artifacts and processing this information, e.g., to check the correctness and consistency of variability information or to apply metrics. A configuration-based setup along with automatic documentation functionality allows different experiments and supports their easy reproduction. Here, we describe KernelHaven as a product line analysis research tool and highlight its basic approach as well as its fundamental capabilities. In particular, we describe available information extraction and processing plug-ins and how to combine them. On this basis, researchers and interested professional users can rapidly conduct a first set of experiments. Further, we describe the concepts for extending KernelHaven by new plug-ins, which reduces development effort when realizing new experiments.

Support for complex product line populations

In this paper, we describe EASy-Producer, a prototypical tool for complex and large-scale Software Product Line (SPL) development. The tool enables SPL engineers to reduce complexity by combining derivation and composition techniques to manage one large SPL as a combination of individual, but interrelated SPLs.

Identifying the intensity of variability changes in software product line evolution

The evolution of a Software Product Line (SPL) typically affects a variety of artifact types. The intensity (the frequency and the amount) in which developers change variability information in these different types of artifacts is currently unknown. In this paper, we present a fine-grained approach for the variability-centric extraction and analysis of changes to code, build, and variability model artifacts introduced by commits. This approach complements existing work that is typically based on a feature-perspective and, thus, abstracts from this level of detail. Further, it provides a detailed understanding of the intensity of changes affecting variability information in these types of artifacts. We apply our approach to the Linux kernel revealing that changes to variability information occur infrequently and only affect small parts of the analyzed artifacts. Further, we outline how these results may improve certain analysis and verification tasks during SPL evolution.

Model-based product line development with EASy-producer using VIL and VTL

EASy-Producer is an open-source research toolset for engineering product lines, variability-rich software ecosystems, and dynamic software product lines. In this tutorial, we will focus on its model-based development and implementation capabilities, which are realized by the Variability Instantiation Language (VIL) and the Variability Template Language (VTL). Further, we will provide a basic introduction into the Integrated Variability Modeling Language (IVML) in order to use the provided information of IVML variability models and configurations during instantiation defined with VIL and as part of the templates created with VTL.

Variability modeling with the integrated variability modeling language (IVML) and EASy-producer

EASy-Producer is an open-source research toolset for engineering product lines, variability-rich software ecosystems, and dynamic software product lines. In this tutorial, we will focus on its (textual) variability modeling capabilities as well as its configuration and validation functionality. Further, we will provide an outlook on how EASy-Producer can be applied to variability instantiation.