Test scenario generation for feature-based context-oriented software systems

To tame the complexity of engineering customizable software, systems are built as families of products that share a common core. As customers desire the automatic and smart adjusting of their software to various contexts of operation, runtime reconfiguration capabilities need to be added. In this extended abstract, we sketch reengineering challenges to be tackled when evolving classic software product lines into such dynamic software product lines.

We envision an Autonomic Software Product Line (ASPL). The ASPL is a dynamic software product line that supports self adaptable products. We plan to use reflective architecture to model and develop ASPL. To evaluate the approach, we have implemented three autonomic product lines which show promising results. The ASPL approach is at initial stages, and require additional work. We plan to exploit online learning to realize more dynamic software product lines to cope with the problem of product line evolution. We propose on-line knowledge sharing among products in a product line to achieve continuous improvement of quality in product line products.

In Dynamic Software Product Lines (DSPLs) product configuration occurs at runtime. Modelling variability and configuring the product in DSPLs should consider the context and non-functional requirements (NFRs) satisfaction. ConG4DaS (Contextual Goal models For Dynamic Software product lines) is a Requirements Engineering (RE) approach for DSPL which supports (i) modelling of variability with goals, NFRs, contexts and the relationship between them; and (ii) offers a product configuration based on contexts, NFRs and their priority and interactions. In this paper, we present a survey evaluation of ConG4DaS with RE and DSPL researchers in regard to the perceived usefulness. In the survey, both RE and DSPL researchers perceived ConG4DaS as useful for modelling and configuring DSPLs. However, the RE group gave more positive answers than the his study presents the report about a case study on the application of REACT-M (Requirements Evolution in Agile ContexT - Management), an agile method to support software requirements management, in a real software development environment. This case study assessed the strengths, weaknesses, opportunities, and threats related to the assets that make up REACT-M, namely: work products, life cycle, roles, and ceremonies. About the results, it was observed that REACT-M was effective, simple to use, strongly collaborative, suitable, user centered and goal oriented. Thus, achieved its main purpose to evolve the requirements of a software product in iteratively, efficiently and under of the agile mindset. The results contribute to the software industry by providing empirical data about the use of a agile method to software requirements management, which can serve as a reference for organizations seeking the adoption of agile methods related to the requirements area, as well as to provide the scientific community with a better empirical understanding of the relationship between requirements and agile methodDSPL group.

Emerging domains such as smart homes and more recently smart cities represent a big challenge to software engineering. In such context, the need of runtime self-adaptations to cope with both user needs and environmental changes brings Dynamic Software Product Lines (DSPL) as a suitable solution. However, DSPL implementation itself is challenging, which demands a proper modeling. In this sense, the literature still lacks of means of choosing the modeling technique that best fits a given domain. This paper tackles such problem by defining a criteria for rank such techniques, which is used for ranking a set DSPL modeling techniques found in the literature.

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.

Automating feature model refactoring: A Model transformation approach

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 many 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. In this paper we thus present experiences of developing feature models for two large-scale industrial automation software systems. Specifically, we extended an existing feature modeling tool to support models for different purposes and at multiple levels. We report results on the characteristics and modularity of the feature models, including metrics about model dependencies. We further discuss lessons learned during the modeling process.

Automated diagnosis of feature model configurations

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.

Goal models can capture similarities and the variability of a Software Product Line (SPL), but they cannot describe the detailed behavior of the SPL functionality. Due to this limitation, a process called GS2SPL was defined to systematically obtain, from goal models, feature models and the specification of use case scenarios with variability. However, the variability and the configuration knowledge of the SPL are tangled in the scenarios description, jeopardizing the maintenance and reuse of this artifact. In order to handle with this problem, it was proposed a technique called MSVCM. It specifies the SPL variability and the configuration knowledge separately from the common behavior present in the scenarios, as well as it defines a process to configure the specification of a product. However, there is a lack of traceability between the MSVCM scenarios and the goals and quality that the stakeholder expects to achieve. Thus, this work proposes to obtain, systematically, the specification of MSVCM scenarios from goal models. Using goals in SPL allows a systematic derivation of the SPL requirements from these goals. This new approach is called GAS2SPL and it is illustrated by using the TaRGeT example.

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

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.

Dynamic Software Product Line (DSPL) Engineering has gained interest through its promise of being able to unify software adaptation whereby software adaptation can be realised at compile time and runtime. While previous work has enabled program logic adaptation by the use of language extensions and platform support, little attention has been placed on Graphical User Interface (GUI) variability. Different design patterns including the Model View Controller are commonly used in GUI implementation, with GUI documents being used for declaring the GUI. To handle dynamic GUI variability currently, the developer needs to implement GUI refinements using multiple techniques. This paper proposes a solution for dealing with GUI document variability, statically and dynamically, in a unified way. In our approach, we currently use a compile time method for producing GUI variants, and code transformations to handle these variants within the application at runtime. To avoid GUI duplicates, only GUI variants that are unique, and related to a valid product configuration, are produced. To validate our approach, we implemented tool support to enable this for Android based applications.

Software product lines (SPLs) are families of software systems sharing common assets and exhibiting variabilities specific to each product member of the family. Commonalities and variabilities are often represented as features organized in a feature model. Due to combinatorial explosion of the number of products induced by possible features combinations, exhaustive testing of SPLs is intractable. Therefore, sampling and prioritization techniques have been proposed to generate sorted lists of products based on coverage criteria or weights assigned to features. Solely based on the feature model, these techniques do not take into account behavioural usage of such products as a source of prioritization. In this paper, we assess the feasibility of integrating usage models into the testing process to derive statistical testing approaches for SPLs. Usage models are given as Markov chains, enabling prioritization of probable/rare behaviours. We used featured transition systems, compactly modelling variability and behaviour for SPLs, to determine which products are realizing prioritized behaviours. Statistical prioritization can achieve a significant reduction in the state space, and modelling efforts can be rewarded by better automation. In particular, we used MaTeLo, a statistical test cases generation suite developed at ALL4TEC. We assess feasibility criteria on two systems: Claroline, a configurable course management system, and Sferion™, an embedded system providing helicopter landing assistance.

The design of the variability of a software product line is crucial to its success and evolution. Meaningful variable features need to be elicited, analyzed, documented and validated when an existing software or reference system evolves into a software product line. These variable features are the main discriminators between individual products and they need to reflect the needs of a large variety of stakeholders adequately. In this paper we present a novel approach, called feature unweaving, that supports the identification and extraction of variable features from a given graphical software requirements model. We have extended our aspect-oriented software product line modeling tool such that it supports feature unweaving: it takes a set of model elements that a domain requirements engineer considers to constitute a variable feature and automatically refactors the model into a semantically equivalent one in which the model elements belonging to this feature are grouped into an aspect. This allows the identification and modeling of variable features in an incremental style. It also substantially reduces both the intellectual and clerical effort required for constructing the variable parts of a software product line requirements model.