Mapping feature models onto domain models: ensuring consistency of configured domain models

Feature models are widely used for describing the variability of a software product line. A feature model contains a tree of features and a set of constraints over these features, which define valid feature combinations. In the industrial practice, large feature models containing hundreds of features and constraints are common. Furthermore, in a hierarchical product line a feature model can be related to other feature models through inter-model constraints. Due to the model size and complexity, understanding industrial feature models is a challenging task.In this paper, we describe the feature model understanding challenges reported by feature model developers at Robert Bosch GmbH. To support the developers in model understanding, we extend the idea of a feature implication graph to feature relation graph by abstracting groups of implications to feature relations. A transitively closed relation graph shows all modeled and implicit feature relations and spans all related feature models. The graph is also used to identify modeling problems, such as false optional or dead features, and to show the derivation of any implicit relation or problem from the modeled constraints. In a case study at Bosch, we evaluate the use of feature relation graph for model understanding. We propose further use cases of the graph, supporting model maintenance, evolution and configuration.

Needs for mass customization and economies of scale have pushed engineers to develop Software Product Lines (SPLs). SPLs are families of products sharing commonalities and exhibiting differences, built by reusing software assets abstractly represented by features. Feature models describe the constraints that link the features and allow the configuration of tailored software products. Common SPLs involve hundreds, even thousands of features, leading to billions of possible software products. As a result, testing a product line is challenging due to the enormous size of the possible products. Existing techniques focus on testing based on the product line's feature model by selecting a limited set of products to test. Being created manually or reverse-engineered, feature models are prone to errors impacting the generated test suites. In this paper, we examine ability of test suites to detect such errors. In particular, we propose two mutation operators to derive erroneous feature models (mutants) from an original feature model and assess the capability of the generated original test suite to kill the mutants. Experimentation on real feature models demonstrate that dissimilar tests suites have a higher mutant detection ability than similar ones, thus validating the relevance of similarity-driven product line testing.

Feature models are the de facto standard for modelling variabilities and commonalities in features and relationships in software product lines. They are the base artefacts in many engineering activities, such as product configuration, derivation, or testing. Concrete models in different domains exist; however, many are in private or sparse repositories or belong to discontinued projects. The dispersion of knowledge of feature models hinders the study and reuse of these artefacts in different studies. The Universal Variability Language (UVL) is a community effort textual feature model language that promotes a common way of serializing feature models independently of concrete tools. Open science principles promote transparency, accessibility, and collaboration in scientific research. Although some attempts exist to promote feature model sharing, the existing solutions lack open science principles by design. In addition, existing and public feature models are described using formats not always supported by current tools. This paper presents ▪ , a repository of feature models in UVL format. ▪ provides a front end that facilitates the search, upload, storage, and management of feature model datasets, improving the capabilities of discontinued proposals. Furthermore, the tool communicates with Zenodo – one of the most well-known open science repositories – providing a permanent save of datasets and following open science principles. ▪ includes existing datasets and is readily available to include new data and functionalities in the future. It is maintained by three active universities in variability modelling.

Software product line (SPL) is a software engineering paradigm for software development. A software product within a product line often has specific functionalities that are not common to all other products within the product line. Those specific functionalities are termed “variant features” in a product line. SPL paradigm involves the modeling of variant features. However, little work in SPL investigates and addresses the modeling of variant features specific to user interface (UI). Unified Modeling Language (UML) is the de facto modeling language for object-oriented software systems. It is known that UML needs better support in modeling UIs. Thus, much research developed UML extensions to improve UML support in modeling UIs. Yet little of this work is related to developing such extensions for modeling UIs for SPLs in which variant features specific to UI modeling must be addressed. This research develops a UML extension -Web User Interface Modeling Language (WUIML) to address these problems. WUIML defines elements for modeling variant features specific to user interfaces for Web-based SPLs. The model elements in WUIML extend from the metaclass and BasicActivity of the UML2.0 metamodel. WUIML integrates the modeling of variant features specific to user interfaces to UML. For example, in a Web-based patient registration software product line, member products targeting British users may use British date format in the user interface, while member products targeting United States users may use United States date format in the user interface. Thus, this is a variant feature for this product line. WUIML defines a model element, XOR, to represent such exclusive or conditions in a product line user interface model. WUIML would reduce SPL engineers’ efforts needed in UI development. To validate the WUIML research outcome, a case study was conducted. The results of this empirical study indicate that modeling UIs for Web-based SPLs using WUIML is more effective and efficient than using standard UML.

Software product family or line is a software engineering paradigm that systematizes reuse. In software product line engineering, two phases are distinguished: domain engineering which is in charge of developing a common infrastructure and assets and application engineering which makes use of those assets to generate the products. One of the key aspects of product lines is variability and its management. However, the main focus has been on functional variability and quality variability in software product lines has not received so much attention by researchers. In a product line different members of the line may require different levels of a quality requirement, for instance they could differ in terms of their availability, security, reliability, etc. Due to this variability, quality evaluation in software product lines is much more complicated that in single-systems. One alternative is to evaluate all the products of a line but it is very expensive and ways of reducing evaluation efforts are necessary. In this direction, the paper presents a method for facilitating cost-effective quality evaluation of a product line taking into consideration variability on quality attributes.

Software product lines are able to describe multiple products sharing a common base of features and are commonly described as feature models. For complex software product lines, automatic analyses are required to ensure validity and to improve the interactive configuration process. Modern SAT solvers are vital components for the validation process of feature models. The increasing variability of software product lines implies the need to use more expressive solvers like SMT solvers. To assist the development of feature modeling tools, we compare SAT and SMT solvers for the automated analysis of feature models. During this thesis, we create an abstract data type to formally define analyses for feature model defects and their explanations. The result shows that SAT solvers are more efficient at detecting the defects, while SMT solvers can find explanations for them multiple times faster. Feature models can be further expanded by attaching attributes to features. Such attributes may contain a numerical value. Additionally, one attribute can be defined for multiple features. In this thesis, we aim to support the interactive configuration process, by providing the range of the sum of values for an attribute. Such ranges depend on the remaining choices in a configuration of the product line. We provide an exact computation using SMT and an approximation using a heuristic. The evaluation results show that an SMT solver is not suitable for supporting interactive configuration. However, the approximated ranges of the provided heuristic were very close to the exact ones.

Trusted Product Lines

Lately, the demand for mobile applications development has increased significantly mainly due to growth of use of mobile devices and the need to port existing web applications. To reduce development’s time and cost, Software Product Lines (SPLs) have also been used in the context of mobile applications. However, the existing SPLs do not worry about supporting the development of mobile applications corresponding to the existing Web applications, as it is desirable to have access to the information and main features of these applications in mobile devices. In face of this problem, this paper discusses the motivation and presents the evolution from a SPL in the e-Gov Web (e-Gov Web SPL) domain to a SPL in the mobile domain (e-Gov Mobile SPL) having in mind the need to supply market demand. The conducted evolution was supported by the PLUS approach (Product Line UML-Based Software Engineering) and by the features model. Furthermore, this work debates the main results obtained through some e-Gov Mobile SPL instantiations in the precision livestock domain.KeywordsSoftware Product LineEvolutione-GovWebMobile

For the development of variable systems, software product lines (SPL) are an established way to handle the variability by using feature models. Nevertheless, the configuration of an SPL can be complex, especially if a product line consists of a large number of features. The problem of handling the complexity becomes even more sophisticated if not only software, but also mechatronic systems containing software and hardware components are configured. Besides modeling the software, within a mechatronic system dependencies and associations between software and hardware features need to be considered which further increases the complexity. To handle this complexity in product lines for mechatronic systems, we propose a multi product line (MPL) approach which allows to distinguish between software and hardware by using different feature models for each. In addition we introduce a level of abstraction to complex product lines consisting of multiple feature models by establishing a feature model mapping. In this paper we present details to the mapping to provide an abstract configuration view as well as the introduced associations for our MPL approach.

Domain engineering is the core technology of systematic software reuse and the precedent period of software requirements engineering. FODA method and other FODA-based methods of domain analysis have made great progress. In these methods, feature model and feature-oriented modeling methodology are widely accepted. However, they have three limitations: 1) Feature model cannot be applied separately, it must work together with other models, such as entity-relationship model and function model to present the whole domain. 2) Feature model is a conceptual tree model, which needs standardized description mechanism to support better conversion to domain design, domain implementation and application engineering. 3) With the service-oriented method permeating into current software development process, traditional domain model encounters challenges in providing more effective reuse to service-oriented software requirements activities. To solve these problems, we proposed to combine service-oriented method and domain engineering together, introduced a new concept of Domain Service, and gave its acquisition process and OWL-S based ontology definition. Domain Service is acquired from the classic feature model and could encapsulate features and their relations to model domain commonalities and differences. OWL-S based specification of Domain Service enhances the application of domain model. After Domain Service acquisition and specification, we can get a domain model composed of a set of Domain Services with different granularity. The model has two layers: Domain Service Layer and Ontology Layer, which can be mapped to the domain model produced from the FODA method. Finally, we applied our method in the domain of Public Travel Information Systems.

Automating feature model refactoring: A Model transformation approach

Evaluating the quality of software product line (SPL) feature models is essential because a low quality design will be eventually reflected in almost all the products of the family. Assessment of usability in particular improves reusability which is the ultimate aim of SPL. Because feature models are used in the early stages of development, their usability assessment will help developers to design highly useable product lines. In this paper, it is proposed to develop a prediction model which can be used to forecast the usability of feature models. In our previous work we had proposed metrics for usability assessment of feature models. In this current work, we have used these metrics to develop and compare prediction accuracy of five machine learning algorithms in terms of usability and predict usability of feature models on the basis of the best performing model.

Automated diagnosis of feature model configurations

A Software Product Line (SPL) is a set of systems that share a group of manageable features and satisfy the specific needs of a particular domain. The features of an SPL can be used in variable combinations to derive product variants in the SPL domain. Because SPLs promote product development through reuse, it is vital to have a means to measure their quality in terms of quality attributes like complexity, reusability,… In this paper, we propose a set of metrics to evaluate the quality of an SPL at three levels: the feature model, design and code. We adapted a set of metrics for software quality and defined new metrics to deal with the inherent characteristics of SPLs, specifically the feature model and the traceability between features, design and code. Furthermore, to assist in interpreting the quality of a given SPL, we conducted an empirical study over ten open source SPLs to identify thresholds for the proposed metrics.

Feature models are commonly used to specify variability in software product lines. Several tools support feature models for variability management at different steps in the development process. However, tool support for test configuration generation is currently limited. This test generation task consists in systematically selecting a set of configurations that represent a relevant sample of the variability space and that can be used to test the product line. In this paper we propose \pw tool to analyze feature models and automatically generate a set of configurations that cover all pair wise interactions between features. \pw tool relies on constraint programming to generate configurations that satisfy all constraints imposed by the feature model and to minimize the set of the tests configurations. This work also proposes an extensive experiment, based on the state-of-the art SPLOT feature models repository, showing that \pw tool scales over variability spaces with millions of configurations and covers pair wise with less configurations than other available tools.