Trusted Product Lines

Automating feature model refactoring: A Model transformation approach

Identifying features and creating a feature model during the process of software product line engineering is time-consuming and requires substantial effort from modelers. In recent years, a number of approaches that map goal models to feature models have been proposed so as to avoid creating the feature model from scratch. However, these approaches can only map part of the elements, such as the goals. The question of how to map the dependencies among actors to the feature model remains an open problem. In this paper, we exploit the standard goal-oriented framework, i.e., the i* framework, for constructing a more complete domain feature model. In particular, we propose mapping rules as well as an algorithm for mapping dependencies among actors to the feature model. In addition, we seek to customize the application products using the i* model evaluation approach during the application engineering phase. The case shows that our approach is practical and efficient.

The design of mechatronic products requires cooperation and coordination of the involved disciplines. To analyze the dynamic behavior of the product’s subsystems and their components, multiple dynamic behavior models (DBM) are developed in different levels of detail (modeling depths) and domains. However, in order to simulate the complex interactions and dependencies between them, models of the whole system are needed, which fit the varying modeling objectives and analysis goals. These comprehensive models are often extensive and the manual construction presupposes deep insight in the specific model approaches and modeling tools. Furthermore, consistency needs to be ensured. The paper describes a way to automatically configure simulation models of the system adopting a Software Product Line (SPL) approach. With the use of feature models, SPL approach provides a structured method for managing variability. The particular focus of this paper is on handling of components in different tools with more than one level of detail through deployment of feature modeling. Also, it presents the concept of a multifunctional model client (MMC), which facilitates integration of solution and system knowledge.

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.

The demand of new Social Networking Service (SNS) is high because the SNSs have been popular these days. In order to deliver various SNSs as early as possible, software product line (SPL) approach can be useful. By using the state of the practices of SPL, this paper shows how to manage commonalities and variabilities of SNS. Specifically, to make an architecture design, presented practices include: understanding relevant domains, requirements engineering, architecture definition. The strengths and weaknesses of Face book architecture are evaluated with the Architecture Tradeoff Analysis Method (ATAM). As a result of applying a framework for SPL practice, layered view and component-based view are illustrated along with variabilities represented by Product Line UML-based Software Engineering (PLUS) and Orthogonal Variability Model (OVM). Based on the analysis of requirements of SNS, additional services such as file sharing and instant messaging are represented as optional components. In case of Face book, three key quality attributes, i.e., availability, scalability, and privacy are analyzed by using quality attribute utility tree. We identified that Face book employs client-server architecture. Through ATAM, Peer-to-Peer (P2P) approach promoting privacy is explained.

Software product lines and model transformations are two techniques used in industry for managing the development of highly complex software. Product line approaches simplify the handling of software variants while model transformations automate software manipulations such as refactoring, optimization, code generation, etc. While these techniques are well understood independently, combining them to get the benefit of both poses a challenge because most model transformations apply to individual models while model-level product lines represent sets of models. In this paper, we address this challenge by providing an approach for automatically ``lifting'' model transformations so that they can be applied to product lines. We illustrate our approach using a case study and evaluate it through a set of experiments.

This report explains the challenges experienced as Overwatch Textron Systems transitioned to a software product line approach. Overwatch Textron Systems provides both software products and custom software development in the domain of intelligence planning, collection and analysis to the U.S. Government and its allies. This report: a) Describes the approach taken to transition Overwatch Textron Systems to a product line organization. b) Provides an overview of the Overwatch Textron Systems software product line; the Overwatch Intelligence Center. c) Describes the product line architecture that is key to the Overwatch Intelligence Center software product line. d) Provides a summary of the lessons learned during the transition.

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.

Software product line adoption is a challenging task in software development organisations. There are some reports in the literature of how software product line engineering has been adopted in several companies using different variability management techniques and patterns. However, to the best of our knowledge, there are no empirical reports on how variability management is handled in companies that do not know about software product line methods and tools. In this paper we present an experience report observing variability management practices in a software development company that was unaware of software product line approaches. We briefly report how variability management is performed in different areas ranging from business architecture to software assets management. From the observation we report some open research opportunities for the future and foster further similar and more structured empirical studies on unaware software product line companies.

Done well, the blend of Model Driven Development (MDD) and Software Product Lines (SPL) offers a promising approach, mixing abstraction from MDD and variability from SPL. Although Model Driven Product Lines have flourished recently, the focus so far has been mostly on how to cope with the variability of models. This focus on model variability has limited however the extension of variability to further artifacts apart from models such as metamodels and model transformations, that may cope with variability too in a product line setting. In this paper, we address the application of feature-oriented refinement to models, metamodels and model transformations. We illustrate our work with a case study of an embedded system.

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.

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.

Pervasive applications will be naturally integrated as part of our environment. On the one hand, they will be deployed into a diversity of small devices and appliances, and on the other hand, they must be aware of highly changing execution contexts. Therefore pervasive computing requires the definition of advance mechanisms that support, (1) the deployment of pervasive applications through various devices with different capacities, and (2) the runtime reconfiguration for dealing with context changes. A software product line approach would be very useful to express the different requirements of devices in terms of commonalities and variabilities of a middleware platforms family. A feature model for pervasive applications will help both to deploy various configurations of the middleware tailored to each device, and to support the dynamic reconfiguration according to context. But, several crosscutting variable features and dependencies between features are commonly found in pervasive computing, (e.g. security, context-awareness, fault-tolerance, etc.). To address this problem we propose a family of aspect-oriented middleware platforms, able to deal with the high dynamic issue of pervasive systems. In this paper we will focus on the feature model definition and we also outline its mapping to a dynamic aspect-oriented middleware platform.

The emerging Internet of Things (IoT) has facilitated an explosion of everyday items now augmented with networking and computational features. Some of these devices are developed using a Software Product Line (SPL) approach in which each device, or product, is instantiated with unique features while reusing a common core. The need to rapidly develop and deploy these systems in order to meet customer demand and reach niche markets first requires shortened development schedules. However, many of these systems perform roles requiring thorough verification, for example, securing homes. In these systems, the detection and correction of errors early in the development life cycle is essential to the success of such projects, with particular emphasis on the requirements and design phases where approximately 70% of faults are introduced. Tools such as the Architecture Analysis & Design Language (AADL) and its verification utilities aid in the development of an assured design for embedded systems. However, while AADL has excellent support for the specification of SPLs, current verification utilities for AADL do not fully support SPLs, particularly SPL models utilizing composition. We introduce an extended version of AGREE, a verification utility for AADL, with support for compositional verification of SPLs.

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.