Variability and Evolution in Systems of Systems

In this position paper (1) we discuss two particular aspects of Systems of Systems, i.e., variability and evolution. (2) We argue that concepts from Product Line Engineering and Software Evolution are relevant to Systems of Systems Engineering. (3) Conversely, concepts from Systems of Systems Engineering can be helpful in Product Line Engineering and Software Evolution. Hence, we argue that an exchange of concepts between the disciplines would be beneficial.Comment: In Proceedings AiSoS 2013, arXiv:1311.319

Capturing the requirements for multiple user interfaces

non-peer-reviewedIn this paper we describe MANTRA, a model-driven approach for the development of multiple consistent user interfaces for one application. The common requirements of all these user interfaces are captured in an abstract UI model (AUI) which is annotated with constraints on the dialogue flow. We exemplify all further steps along a well known application scenario in which a user queries train connections from a simple timetable service. We consider in particular how the user interface can be adapted on the AUI level by deriving and tailoring dialogue structures which take into account constraints imposed by front-end platforms or inexperienced users. With this input we use model transformations to derive concrete, platform-specific UI models (CUI). These can be used to generate implementation code for several UI platforms including GUI applications, dynamic websites and mobile applications. The user interfaces are integrated with a multi tier application by referencing WSDL-based (Web Service Description Language) interface descriptions. Finally, we discuss how our approach can be extended to include voice interfaces. This imposes special challenges as these interfaces tend to be structurally different from visual platforms and have to be specified using speech-input grammars

Mobile RFID Management – An Application Scenario on the Handling of Industrial Liquid Containers

This paper deals with concepts, challenges and design alternatives for the application of RFID technology within an industry context. We are especially interested in the combination of RFID technology with positioning information and mobile networks. To discuss these topics, we introduce an application scenario concerning the handling of industrial liquid containers along an integrated supply chain. First we describe the traditional approach and some of the problems involved with it. We then contrast this with an improved process using RFID technology. The scenario is augmented by a discussion of an appropriate application prototype. This paper thus contributes to the debate on RFID and highlights the challenges of integrating various mobile technologies in order to efficiently support supply chain processes

CASE Tool support for variability management in software product lines

Software product lines (SPL) aim at reducing time-to-market and increasing software quality through extensive, planned reuse of artifacts. An essential activity in SPL is variability management, i.e., defining and managing commonality and variability among member products. Due to the large scale and complexity of today’s software-intensive systems, variability management has become increasingly complex to conduct. Accordingly, tool support for variability management has been gathering increasing momentum over the last few years and can be considered a key success factor for developing and maintaining SPLs. While several studies have already been conducted on variability management, none of these analyzed the available tool support in detail. In this work, we report on a survey in which we analyzed 37 existing variability management tools identified using a systematic literature review to understand the tools’ characteristics, maturity, and the challenges in the field. We conclude that while most studies on variability management tools provide a good motivation and description of the research context and challenges, they often lack empirical data to support their claims and findings. It was also found that quality attributes important for the practical use of tools such as usability, integration, scalability, and performance were out of scope for most studies

Reparation in evolutionary algorithms for multi-objective feature selection in large software product lines

Software Product Lines Engineering is the area of software engineering that aims to systematise the modelling, creation and improvement of groups of interconnected software systems by formally expressing possible alternative products in the form of Feature Models. Deriving a software product/system from a feature model is called Feature Configuration. Engineers select the subset of features (software components) from a feature model that suits their needs, while respecting the underlying relationships/constraints of the system–which is challenging on its own. Since there exist several (and often antagonistic) perspectives on which the quality of software could be assessed, the problem is even more challenging as it becomes a multi-objective optimisation problem. Current multi-objective feature selection in software product line approaches (e.g., SATIBEA) combine the scalability of a genetic algorithm (IBEA) with a solution reparation approach based on a SAT solver or one of its derivatives. In this paper, we propose MILPIBEA, a novel hybrid algorithm which combines IBEA with the accuracy of a mixed-integer linear programming (MILP) reparation. We show that the MILP reparation modifies fewer features from the original infeasible solutions than the SAT reparation and in a shorter time. We also demonstrate that MILPIBEA outperforms SATIBEA on average on various multi-objective performance metrics, especially on the largest feature models. The other major challenge in software engineering in general and in software product lines, in particular, is evolution. While the change in software components is common in the software engineering industry, the particular case of multi-objective optimisation of evolving software product lines is not well-tackled yet. We show that MILPIBEA is not only able to better take advantage of the evolution than SATIBEA, but it is also the one that continues to improve the quality of the solutions when SATIBEA stagnates. Overall, IBEA performs better when combined with MILP instead of SAT reparation when optimising the multi-objective feature selection in large and evolving software product lines

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

Context In industrial settings products are developed by more than one organization. Software vendors and suppliers commonly typically maintain their own product lines, which contribute to a larger (multi) product line or software ecosystem. It is unrealistic to assume that the participating organizations will agree on using a specific variability modeling technique—they will rather use different approaches and tools to manage the variability of their systems. Objective We aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations. Method We present an integrative approach that provides a unified perspective to users configuring products in multi product line environments, regardless of the different modeling methods and tools used internally. We also present a technical infrastructure and a prototype implementation based on web services. Results We show the feasibility of the approach and its implementation by using it with the three most widespread types of variability modeling approaches in the product line community, i.e., feature-based, OVM-style, and decision-oriented modeling. To demonstrate the feasibility and flexibility of our approach, we present an example derived from industrial experience in enterprise resource planning. We further applied the approach to support the configuration of privacy settings in the Android ecosystem based on multiple variability models. We also evaluated the performance of different model enactment strategies used in our approach. Conclusions Tools and techniques allowing stakeholders to handle variability in a uniform manner can considerably foster the initiation and growth of software ecosystems from the perspective of software reuse and configuration.Ministerio de Economía y Competitividad TIN2012-32273Junta de Andalucía TIC-186

Lazy product discovery in huge configuration spaces

Highly-configurable software systems can have thousands of inter-dependent configuration options across different subsystems. In theresulting configuration space, discovering a valid product configu-ration for some selected options can be complex and error prone.The configuration space can be organized using a feature model,fragmented into smaller interdependent feature models reflectingthe configuration options of each subsystem.We propose a method for lazy product discovery in large frag-mented feature models with interdependent features. We formalizethe method and prove its soundness and completeness. The evalu-ation explores an industrial-size configuration space. The resultsshow that lazy product discovery has significant performance ben-efits compared to standard product discovery, which in contrastto our method requires all fragments to be composed to analyzethe feature model. Furthermore, the method succeeds when moreefficient, heuristics-based engines fail to find a valid configuration

Towards a Secure DevOps Approach for Cyber-Physical Systems: An Industrial Perspective

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