A Systematic Review of Tracing Solutions in Software Product Lines

Software Product Lines are large-scale, multi-unit systems that enable massive, customized production. They consist of a base of reusable artifacts and points of variation that provide the system with flexibility, allowing generating customized products. However, maintaining a system with such complexity and flexibility could be error prone and time consuming. Indeed, any modification (addition, deletion or update) at the level of a product or an artifact would impact other elements. It would therefore be interesting to adopt an efficient and organized traceability solution to maintain the Software Product Line. Still, traceability is not systematically implemented. It is usually set up for specific constraints (e.g. certification requirements), but abandoned in other situations. In order to draw a picture of the actual conditions of traceability solutions in Software Product Lines context, we decided to address a literature review. This review as well as its findings is detailed in the present article.Comment: 22 pages, 9 figures, 7 table

Review of Requirement Engineering Approaches for Software Product Lines

The Software Product Lines (SPL) paradigm is one of the most recent topics of interest for the software engineering community. On the one hand, the Software Product Lines is based on a reuse strategy with the aim to reduce the global time-to-market of the software product, to improve the software product quality, and to reduce the cost. On the other hand, traditional Requirement Engineering approaches could not be appropriated to deal with the new challenges that arises the SPL adoption. In the last years, several approaches have been proposed to cover this limitation. This technical report presents an analysis of specific approaches used in the development of SPL to provide solutions to model variability and to deal with the requirements engineering activities. The obtained results show that most of the research in this context is focused on the Domain Engineering, covering mainly the Feature Modeling and the Scenario Modeling. Among the studied approaches, only one of them supported the delta identification; this fact implies that new mechanisms to incorporate new deltas in the Domain specification are needed. Regarding the SPL adoption strategy, most of the approaches support a proactive strategy. However, this strategy is the most expensive and risk-prone. Finally, most of the approaches were based on modeling requirements with feature models giving less support to other important activities in the requirements engineering process such as elicitation, validation, or verification of requirements. The results of this study provide a wide view of the current state of research in requirements engineering for SPL and also highlight possible research gaps that may be of interest for researchers and practitioners.Blanes Domínguez, D.; Insfrán Pelozo, CE. (2011). Review of Requirement Engineering Approaches for Software Product Lines. http://hdl.handle.net/10251/1023

Domain Specific Languages for Managing Feature Models: Advances and Challenges

International audienceManaging multiple and complex feature models is a tedious and error-prone activity in software product line engineering. Despite many advances in formal methods and analysis techniques, the supporting tools and APIs are not easily usable together, nor unified. In this paper, we report on the development and evolution of the Familiar Domain-Specific Language (DSL). Its toolset is dedicated to the large scale management of feature models through a good support for separating concerns, composing feature models and scripting manipulations. We overview various applications of Familiar and discuss both advantages and identified drawbacks. We then devise salient challenges to improve such DSL support in the near future

Biological data integration using Semantic Web technologies

International audienceCurrent research in biology heavily depends on the availability and efficient use of information. In order to build new knowledge, various sources of biological data must often be combined. Semantic Web technologies, which provide a common framework allowing data to be shared and reused between applications, can be applied to the management of disseminated biological data. However, due to some specificities of biological data, the application of these technologies to life science constitutes a real challenge. Through a use case of biological data integration, we show in this paper that current Semantic Web technologies start to become mature and can be applied for the development of large applications. However, in order to get the best from these technologies, improvements are needed both at the level of tool performance and knowledge modeling

A Framework for Seamless Variant Management and Incremental Migration to a Software Product-Line

Context: Software systems often need to exist in many variants in order to satisfy varying customer requirements and operate under varying software and hardware environments. These variant-rich systems are most commonly realized using cloning, a convenient approach to create new variants by reusing existing ones. Cloning is readily available, however, the non-systematic reuse leads to difficult maintenance. An alternative strategy is adopting platform-oriented development approaches, such as Software Product-Line Engineering (SPLE). SPLE offers systematic reuse, and provides centralized control, and thus, easier maintenance. However, adopting SPLE is a risky and expensive endeavor, often relying on significant developer intervention. Researchers have attempted to devise strategies to synchronize variants (change propagation) and migrate from clone&own to an SPL, however, they are limited in accuracy and applicability. Additionally, the process models for SPLE in literature, as we will discuss, are obsolete, and only partially reflect how adoption is approached in industry. Despite many agile practices prescribing feature-oriented software development, features are still rarely documented and incorporated during actual development, making SPL-migration risky and error-prone.Objective: The overarching goal of this PhD is to bridge the gap between clone&own and software product-line engineering in a risk-free, smooth, and accurate manner. Consequently, in the first part of the PhD, we focus on the conceptualization, formalization, and implementation of a framework for migrating from a lean architecture to a platform-based one.Method: Our objectives are met by means of (i) understanding the literature relevant to variant-management and product-line migration and determining the research gaps (ii) surveying the dominant process models for SPLE and comparing them against the contemporary industrial practices, (iii) devising a framework for incremental SPL adoption, and (iv) investigating the benefit of using features beyond PL migration; facilitating model comprehension.Results: Four main results emerge from this thesis. First, we present a qualitative analysis of the state-of-the-art frameworks for change propagation and product-line migration. Second, we compare the contemporary industrial practices with the ones prescribed in the process models for SPL adoption, and provide an updated process model that unifies the two to accurately reflect the real practices and guide future practitioners. Third, we devise a framework for incremental migration of variants into a fully integrated platform by exploiting explicitly recorded metadata pertaining to clone and feature-to-asset traceability. Last, we investigate the impact of using different variability mechanisms on the comprehensibility of various model-related tasks.Future work: As ongoing and future work, we aim to integrate our framework with existing IDEs and conduct a developer study to determine the efficiency and effectiveness of using our framework. We also aim to incorporate safe-evolution in our operators

Enterprise Model Library for Business-IT-Alignment

The knowledge of the world is passed on through libraries. Accordingly, domain expertise and experiences should also be transferred within an enterprise by a knowledge base. Therefore, models are an established medium to describe good practices for complex systems, processes, and interconnections. However, there is no structured and detailed approach for a design of an enterprise model library. The objective of this work is the reference architecture of a repository for models with function of reuse. It includes the design of the data structure for filing, the processes for administration and possibilities for usage. Our approach enables consistent mapping of requirements into models via meta-data attributes. Furthermore, the adaptation of reference architectures in specific use cases as well as a reconciliation of interrelationships is enabled. A case study with industry demonstrates the practical benefits of reusing work already done. It provides an organization with systematic access to specifications, standards and guidelines. Thus, further development is accelerated and supported in a structured manner, while complexity remains controllable. The presented approach enriches various enterprise architecture frameworks. It provides benefits for development based on models