The DOPLER meta-tool for decision-oriented variability modeling: a multiple case study

The variability of a product line is typically defined in models. However, many existing variability modeling approaches are rigid and don’t allow sufficient domain-specific adaptations. We have thus been developing a flexible and extensible approach for defining product line variability models. Its main purposes are to guide stakeholders through product derivation and to automatically generate product configurations. Our approach is supported by the DOPLER (Decision-Oriented Product Line Engineering for effective Reuse) meta-tool that allows modelers to specify the types of reusable assets, their attributes, and dependencies for their specific system and context. The aim of this paper is to investigate the suitability of our approach for different domains. More specifically, we explored two research questions regarding the implementation of variability and the utility of DOPLER for variability modeling in different domains. We conducted a multiple case study consisting of four cases in the domains of industrial automation systems and business software. In each of these case studies we analyzed variability implementation techniques. Experts from our industry partners then developed domain-specific meta-models, tool extensions, and variability models for their product lines using DOPLER. The four cases demonstrate the flexibility of the DOPLER approach and the extensibility and adaptability of the supporting meta tool.     

Improving software product line configuration: A quality attribute-driven approach

ContextDuring the definition of software product lines (SPLs) it is necessary to choose the components that appropriately fulfil a product’s intended functionalities, including its quality requirements (i.e., security, performance, scalability). The selection of the appropriate set of assets from many possible combinations is usually done manually, turning this process into a complex, time-consuming, and error-prone task.ObjectiveOur main objective is to determine whether, with the use of modeling tools, we can simplify and automate the definition process of a SPL, improving the selection process of reusable assets.MethodWe developed a model-driven strategy based on the identification of critical points (sensitivity points) inside the SPL architecture. This strategy automatically selects the components that appropriately match the product’s functional and quality requirements. We validated our approach experimenting with different real configuration and derivation scenarios in a mobile healthcare SPL where we have worked during the last three years.ResultsThrough our SPL experiment, we established that our approach improved in nearly 98% the selection of reusable assets when compared with the unassisted analysis selection. However, using our approach there is an increment in the time required for the configuration corresponding to the learning curve of the proposed tools.ConclusionWe can conclude that our domain-specific modeling approach significantly improves the software architect’s decision making when selecting the most suitable combinations of reusable components in the context of a SPL.     

Model-based incremental conformance checking to enable interactive product configuration

ContextModel-based product line engineering (PLE) is a paradigm that can enable automated product configuration of large-scale software systems, in which models are used as an abstract specification of commonalities and variabilities of products of a product line.ObjectiveIn the context of PLE, providing immediate feedback on the correctness of a manual configuration step to users has a practical impact on whether a configuration process with tool support can be successfully adopted in practice.MethodIn an existing work, a UML-based variability modeling methodology named as SimPL and an interactive configuration process was proposed. Based on the existing work, we propose an automated, incremental and efficient conformance checking approach to ensure that the manual configuration of a variation point conforms to a set of pre-defined conformance rules specified in the Object Constraint Language (OCL). The proposed approach, named as Zen-CC, has been implemented as an integrated part of our product configuration and derivation tool: Zen-Configurator.ResultsThe performance and scalability of Zen-CC have been evaluated with a real-world case study. Results show that Zen-CC significantly outperformed two baseline engines in terms of performance. Besides, the performance of Zen-CC remains stable during the configuration of all the 10 products of the product line and its efficiency also remains un-impacted even with the growing product complexity, which is not the case for both of the baseline engines.ConclusionThe results suggest that Zen-CC performs practically well and is much more scalable than the two baseline engines and is scalable for configuring products with a larger number of variation points.     

Toward automated feature model configuration with optimizing non-functional requirements

ContextA software product line is a family of software systems that share some common features but also have significant variabilities. A feature model is a variability modeling artifact, which represents differences among software products with respect to the variability relationships among their features. Having a feature model along with a reference model developed in the domain engineering lifecycle, a concrete product of the family is derived by binding the variation points in the feature model (called configuration process) and by instantiating the reference model.ObjectiveIn this work we address the feature model configuration problem and propose a framework to automatically select suitable features that satisfy both the functional and non-functional preferences and constraints of stakeholders. Additionally, interdependencies between various non-functional properties are taken into account in the framework.MethodThe proposed framework combines Analytical Hierarchy Process (AHP) and Fuzzy Cognitive Maps (FCM) to compute the non-functional properties weights based on stakeholders’ preferences and interdependencies between non-functional properties. Afterwards, Hierarchical Task Network (HTN) planning is applied to find the optimal feature model configuration.ResultOur approach improves state-of-art of feature model configuration by considering positive or negative impacts of the features on non-functional properties, the stakeholders’ preferences, and non-functional interdependencies. The approach presented in this paper extends earlier work presented in [1] from several distinct perspectives including mechanisms handling interdependencies between non-functional properties, proposing a novel tooling architecture, and offering visualization and interaction techniques for representing functional and non-functional aspects of feature models.Conclusionour experiments show the scalability of our configuration approach when considering both functional and non-functional requirements of stakeholders.     

Software engineering beyond the project – Sustaining software ecosystems

ContextThe main part of software engineering methods, tools and technologies has developed around projects as the central organisational form of software development. A project organisation depends on clear bounds regarding scope, participants, development effort and lead-time. What happens when these conditions are not given? The article claims that this is the case for software product specific ecosystems. As software is increasingly developed, adopted and deployed in the form of customisable and configurable products, software engineering as a discipline needs to take on the challenge to support software ecosystems.ObjectiveThe article provides a holistic understanding of the observed and reported practices as a starting point to device specific support for the development in software ecosystems.MethodA qualitative interview study was designed based on previous long-term ethnographical inspired research.ResultsThe analysis results in a set of common features of product development and evolution despite differences in size, kind of software and business models. Design is distributed and needs to be coordinated across heterogeneous design constituencies that, together with the software, build a product specific socio-technical ecosystem. The technical design has to support the deference of part of the development not only to 3rd-party developers but also to local designers tailoring the software in the use organisation. The technical interfaces that separate the work of different design constituencies are contested and need to be maintained permanently. Development takes place as cycles within cycles – overlaying development cycles with different rhythms to accommodate different evolution drivers.ConclusionThe reported practices challenge some of the very core assumptions of traditional software engineering, but makes perfect sense, considering that the frame of reference for product development is not a project but continuous innovation across the respective ecosystem. The article provides a number of concrete points for further research.     

Efficient synthesis of feature models

ContextVariability modeling, and in particular feature modeling, is a central element of model-driven software product line architectures. Such architectures often emerge from legacy code, but, creating feature models from large, legacy systems is a long and arduous task. We describe three synthesis scenarios that can benefit from the algorithms in this paper.ObjectiveThis paper addresses the problem of automatic synthesis of feature models from propositional constraints. We show that the decision version of the problem is NP-hard. We designed two efficient algorithms for synthesis of feature models from CNF and DNF formulas respectively.MethodWe performed an experimental evaluation of the algorithms against a binary decision diagram (BDD)-based approach and a formal concept analysis (FCA)-based approach using models derived from realistic models.ResultsOur evaluation shows a 10 to 1,000-fold performance improvement for our algorithms over the BDD-based approach. The performance of the DNF-based algorithm was similar to the FCA-based approach, with advantages for both techniques. We identified input properties that affect the runtimes of the CNF- and DNF-based algorithms.ConclusionsOur algorithms are the first known techniques that are efficient enough to be used on dependencies extracted from real systems, opening new possibilities of creating reverse engineering and model management tools for variability models.     

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.     

Current state and potential of variability management practices in software-intensive SMEs: Results from a regional industrial survey

ContextMore and more, small and medium-sized enterprises (SMEs) are using software to augment the functionality of their products and offerings. Variability management of software is becoming an interesting topic for SMEs with expanding portfolios and increasingly complex product structures. While the use of software product lines to resolve high variability is well known in larger organizations, there is less known about the practices in SMEs.ObjectiveThis paper presents results from a survey of software developing SMEs. The purpose of the paper is to provide a snapshot of the current awareness and practices of variability modeling in organizations that are developing software with the constraints present in SMEs.MethodA survey with questions regarding the variability practices was distributed to software developing organizations in a region of Sweden that has many SMEs. The response rate was 13% and 25 responses are used in this analysis.ResultsWe find that, although there are SMEs that develop implicit software product lines and have relatively sophisticated variability structures for their solution space, the structures of the problem space and the product space have room for improvement.ConclusionsThe answers in the survey indicate that SMEs are in situations where they can benefit from more structured variability management, but the awareness need to be raised. Even though the problem space similarity is high, there is little reuse and traceability activities performed. The existence of SMEs with qualified variability management and product line practices indicates that small organizations are capable to apply such practices.     

SimPL: A product-line modeling methodology for families of integrated control systems

ContextIntegrated control systems (ICSs) are heterogeneous systems where software and hardware components are integrated to control and monitor physical devices and processes. A family of ICSs share the same software code base, which is configured differently for each product to form a unique installation. Due to the complexity of ICSs and inadequate automation support, product configuration in this context is typically error-prone and costly.ObjectiveAs a first step to overcome these challenges, we propose a UML-based product-line modeling methodology that provides a foundation for semi-automated product configuration in the specific context of ICSs.MethodWe performed a comprehensive domain analysis to identify characteristics of ICS families, and their configuration challenges. Based on this, we formulated the characteristics of an adequate configuration solution, and derived from them a set of modeling requirements for a model-based solution to configuration. The SimPL methodology is proposed to fulfill these requirements.ResultsTo evaluate the ability of SimPL to fulfill the modeling requirements, we applied it to a large-scale industrial case study. Our experience with the case study shows that SimPL is adequate to provide a model of the product family that meets the modeling requirements. Further evaluation is still required to assess the applicability and scalability of SimPL in practice. Doing this requires conducting field studies with human subjects and is left for future work.ConclusionWe conclude that configuration in ICSs requires better automation support, and UML-based approaches to product family modeling can be tailored to provide the required foundation.     

一种基于UML的软件产品线可变性建模方法

将UML引入到软件产品线开发中,在产品线可变性分析的基础上,提出了一种基于UML的产品线可变性建模方法。该方法不仅支持可选、多选一等可变点类型的描述,还支持软件产品线可变性的约束建模。在此基础上,还通过一个手机应用软件的产品线可变性建模实例验证了该方法的有效性。     

Combining service-orientation and software product line engineering: A systematic mapping study

ContextService-Orientation (SO) is a rapidly emerging paradigm for the design and development of adaptive and dynamic software systems. Software Product Line Engineering (SPLE) has also gained attention as a promising and successful software reuse development paradigm over the last decade and proven to provide effective solutions to deal with managing the growing complexity of software systems.ObjectiveThis study aims at characterizing and identifying the existing research on employing and leveraging SO and SPLE.MethodWe conducted a systematic mapping study to identify and analyze related literature. We identified 81 primary studies, dated from 2000–2011 and classified them with respect to research focus, types of research and contribution.ResultThe mapping synthesizes the available evidence about combining the synergy points and integration of SO and SPLE. The analysis shows that the majority of studies focus on service variability modeling and adaptive systems by employing SPLE principles and approaches.In particular, SPLE approaches, especially feature-oriented approaches for variability modeling, have been applied to the design and development of service-oriented systems. While SO is employed in software product line contexts for the realization of product lines to reconcile the flexibility, scalability and dynamism in product derivations thereby creating dynamic software product lines.ConclusionOur study summarizes and characterizes the SO and SPLE topics researchers have investigated over the past decade and identifies promising research directions as due to the synergy generated by integrating methods and techniques from these two areas.     

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.     

Characteristics of software ecosystems for Federated Embedded Systems: A case study

ContextTraditionally, Embedded Systems (ES) are tightly linked to physical products, and closed both for communication to the surrounding world and to additions or modifications by third parties. New technical solutions are however emerging that allow addition of plug-in software, as well as external communication for both software installation and data exchange. These mechanisms in combination will allow for the construction of Federated Embedded Systems (FES). Expected benefits include the possibility of third-party actors developing add-on functionality; a shorter time to market for new functions; and the ability to upgrade existing products in the field. This will however require not only new technical solutions, but also a transformation of the software ecosystems for ES.ObjectiveThis paper aims at providing an initial characterization of the mechanisms that need to be present to make a FES ecosystem successful. This includes identification of the actors, the possible business models, the effects on product development processes, methods and tools, as well as on the product architecture.MethodThe research was carried out as an explorative case study based on interviews with 15 senior staff members at 9 companies related to ES that represent different roles in a future ecosystem for FES. The interview data was analyzed and the findings were mapped according to the Business Model Canvas (BMC).ResultsThe findings from the study describe the main characteristics of a FES ecosystem, and identify the challenges for future research and practice.ConclusionsThe case study indicates that new actors exist in the FES ecosystem compared to a traditional supply chain, and that their roles and relations are redefined. The business models include new revenue streams and services, but also create the need for trade-offs between, e.g., openness and dependability in the architecture, as well as new ways of working.     

MOD2-SCM: A model-driven product line for software configuration management systems

ContextSoftware Configuration Management (SCM) is the discipline of controlling the evolution of large and complex software systems. Over the years many different SCM systems sharing similar concepts have been implemented from scratch. Since these concepts usually are hard-wired into the respective program code, reuse is hardly possible.ObjectiveOur objective is to create a model-driven product line for SCM systems. By explicitly describing the different concepts using models, reuse can be performed on the modeling level. Since models are executable, the need for manual programming is eliminated. Furthermore, by providing a library of loosely coupled modules, we intend to support flexible composition of SCM systems.MethodWe developed a method and a tool set for model-driven software product line engineering which we applied to the SCM domain. For domain analysis, we applied the FORM method, resulting in a layered feature model for SCM systems. Furthermore, we developed an executable object-oriented domain model which was annotated with features from the feature model. A specific SCM system is configured by selecting features from the feature model and elements of the domain model realizing these features.ResultsDue to the orthogonality of both feature model and domain model, a very large number of SCM systems may be configured. We tested our approach by creating instances of the product line which mimic wide-spread systems such as CVS, GIT, Mercurial, and Subversion.ConclusionThe experiences gained from this project demonstrate the feasibility of our approach to model-driven software product line engineering. Furthermore, our work advances the state of the art in the domain of SCM systems since it support the modular composition of SCM systems at the model rather than the code level.     

Issue-based variability management

ContextVariability management is a key activity in software product line engineering. This paper focuses on managing rationale information during the decision-making activities that arise during variability management. By decision-making we refer to systematic problem solving by considering and evaluating various alternatives. Rationale management is a branch of science that enables decision-making based on the argumentation of stakeholders while capturing the reasons and justifications behind these decisions.ObjectiveDecision-making should be supported to identify variability in domain engineering and to resolve variation points in application engineering. We capture the rationale behind variability management decisions. The captured rationale information is useful to evaluate future changes of variability models as well as to handle future instantiations of variation points. We claim that maintaining rationale will enhance the longevity of variability models. Furthermore, decisions should be performed using a formal communication between domain engineering and application engineering.MethodWe initiate the novel area of issue-based variability management (IVM) by extending variability management with rationale management. The key contributions of this paper are: (i) an issue-based variability management methodology (IVMM), which combines questions, options and criteria (QOC) and a specific variability approach; (ii) a meta-model for IVMM and a process for variability management and (iii) a tool for the methodology, which was developed by extending an open source rationale management tool.ResultsRationale approaches (e.g. questions, options and criteria) guide distributed stakeholders when selecting choices for instantiating variation points. Similarly, rationale approaches also aid the elicitation of variability and the evaluation of changes. The rationale captured within the decision-making process can be reused to perform future decisions on variability.ConclusionIVMM was evaluated comparatively based on an experimental survey, which provided evidence that IVMM is more effective than a variability modeling approach that does not use issues.     

Weaving variability into domain metamodels

Domain-specific modeling languages (DSMLs) are the essence of MDE. A DSML describes the concepts of a particular domain in a metamodel, as well as their relationships. Using a DSML, it is possible to describe a wide range of different models that often share a common base and vary on some parts. On the one hand, some current approaches tend to distinguish the variability language from the DSMLs themselves, implying greater learning curve for DSMLs stakeholders and a significant overhead in product line engineering. On the other hand, approaches integrating variability in DSMLs lack generality and tool support. We argue that aspect-oriented modeling techniques enabling flexible metamodel composition and results obtained by the software product line community to manage and resolve variability form the pillars for a solution for integrating variability into DSMLs. In this article, we consider variability as an independent and generic aspect to be woven into the DSML. In particular, we detail how variability is woven and how to perform product line derivation. We validate our approach through the weaving of variability into two different metamodels: Ecore??widely used for DSML definition??and SmartAdapters, our aspect model weaver. These results emphasize how new abilities of the language can be provided by this means.     

Bridges and barriers to hardware-dependent software ecosystem participation – A case study

BackgroundSoftware ecosystems emerged as means for several actors to jointly provide more value to the market than any of them can do on its own. Recently, software ecosystems are more often used to support the development of hardware-dependent solutions.ObjectivesThis work aims at studying barriers and bridges to participation in an ecosystem with substantial hardware dependencies.MethodWe conducted an interview-based case study of an ecosystem around Axis’ network video surveillance systems, interviewing 10 internal experts and 8 external representatives of 6 companies, complemented by document studies at Axis.ResultsMajor bridges to the ecosystem include end customer demands, open and transparent communication and relationship, as well as internal and external standardizations. Barriers include the two-tier business model, entry barriers and execution performance issues. Approximately half of the identified bridges and barriers could be considered hardware-dependent ecosystems specific.ConclusionOur results suggest that ecosystem leaders should share their sales channels with the ecosystem participants and focus on good communication and relationships as the dominant factors for the ecosystem participation. Moreover, we report that internal and external standardization can play a dual role, not only ease the development but also enable additional sales channels and new opportunities for the ecosystem participants. At the same time, the business model selected by the ecosystem leaders and performance, are identified as the main barriers to ecosystem participation. We believe that the business model barrier may be much more important for similar hardware-dependent software ecosystems.     

The Pro-PD Process Model for Product Derivation within software product lines

BackgroundThe derivation of products from a software product line is a time consuming and expensive activity. Despite recognition that an effective process could alleviate many of the difficulties associated with product derivation, existing approaches have different scope, emphasise different aspects of the derivation process and are frequently too specialised to serve as a general solution.ObjectiveTo define a systematic process that will provide a structured approach to the derivation of products from a software product line, based on a set of tasks, roles and artefacts.MethodThrough a series of research stages using sources in industry and academia, this research has developed a Process Model for Product Derivation (Pro-PD). We document the evidence for the construction of Pro-PD and the design decisions taken. We evaluate Pro-PD through comparison with prominent existing approaches and standards.ResultsThis research presents a Process Model for Product Derivation (Pro-PD). Pro-PD describes the tasks, roles and work artefacts used to derive products from a software product line.ConclusionIn response to a need for methodological support, we developed Pro-PD (Process Model for Product Derivation). Pro-PD was iteratively developed and evaluated through four research stages. Our research is a first step toward an evidence-based methodology for product derivation and a starting point for the definition of a product derivation approach.