Do #ifdef-based Variation Points Realize Feature Model Constraints?

In design, fixation is a recurring problem with novices where they choose the first solution that they think of for a given problem rather than explore a range of possible solutions. Fixation can result in barriers in design process, restricted search and premature commitment to solutions that may be sub-optimal. Among undergraduate engineering students, design fixation is due to limited prior conceptual knowledge, insufficient knowledge of design heuristics, and disconnected and evolving knowledge base, skills and strategies. One mechanism to overcome design fixation is expansion of problem and solution space where learners explore a variety of aspects related to the design problem such as constraints, assumptions, concepts and principles, before deciding on the solution to be followed. To be able to expand problem and solution space, novice designers require support. We have devised a pedagogical strategy flare-fork which scaffolds students’ problem space and solution space expansion in the flare phase and generation of multiple constraint optimized designs in the fork phase. Flare-fork is a systematic process that supports students to build on their opportunistic ideas to expand design boundaries and subsequently identify trade-offs to generate a variety of solutions tailored to fulfill a combination of constraints and assumptions. The pedagogy brings together design strategies, tools and practices such as rapid ideation, shared visual representation, categorization and techniques to restructure thinking patterns in a collaborative environment. In this paper, we first describe the conceptual design of our proposed pedagogy. We then describe a study to examine how the intervention operationalizing the flare phase of the pedagogy supports students in expanding their problem and solution space.

Software product family or line is a software engineering paradigm that systematizes reuse. In software product line engineering, two phases are distinguished: domain engineering which is in charge of developing a common infrastructure and assets and application engineering which makes use of those assets to generate the products. One of the key aspects of product lines is variability and its management. However, the main focus has been on functional variability and quality variability in software product lines has not received so much attention by researchers. In a product line different members of the line may require different levels of a quality requirement, for instance they could differ in terms of their availability, security, reliability, etc. Due to this variability, quality evaluation in software product lines is much more complicated that in single-systems. One alternative is to evaluate all the products of a line but it is very expensive and ways of reducing evaluation efforts are necessary. In this direction, the paper presents a method for facilitating cost-effective quality evaluation of a product line taking into consideration variability on quality attributes.

Software product line (PL) engineering has been established in the last decade as a proven way to build flexibility and reusability into software systems. This approach is centred around the idea that the initial investments made in the development of reusable artefacts are outweighed by the quality and product improvements gained through the reuse of such artefacts. While there are many studies on introducing PL engineering into software development and calculating expected value upfront, there is little documented evidence of long-term experiences with PL engineering. This paper examines perceptions of the value of PL engineering for three PL of different ages. The paper confirms that, while PL engineering enhances product value and quality through shared components and architecture, this is also the predominant limitation of PL engineering. Furthermore, our investigations show that while perceptions of product quality differ depending on PL maturity, this is not the case for time-to-market and cost.

Software Product Line Engineering aims to ensure the correctness, completeness and consistency among its artifacts and the specified domain, in order to prevent the spread of defects for the products derived from this domain. Among initial artifacts of a software product line, feature models are artifacts generated in various domain engineering approaches. Although software inspection is highlighted as an effective review activity for detection of defects in software artifacts, mainly in the early models of software projects, a recent quasi-systematic review of literature indicated a lack of techniques to support the inspection of software product line artifacts, which include features models. Thus, this paper presents FMCheck, a checklist-based inspection technique to support the detection of defects on feature models. This technique was developed to be configurable and to be applied on several extensions of the original feature model notation presented by FODA approach, including the Odyssey-FEX notation, in particular. FMCheck was submitted to a proof of concept and to a further in vitro feasibility study, in which it could be seen the feasibility of FMCheck application and also that inspections applying FMCheck are more effective than ad-hoc inspections, when applied on four distinct domains.

Version control (VC) and Software Product Line Engineering (SPLE) are two software engineering disciplines to manage variability in time and variability in space. In this paper, a thorough comparison of VC and SPLE is provided, showing that both disciplines imply a number of desirable properties. As a proof of concept for the combination of VC and SPLE, we present SuperMod, a tool realizes an existing conceptual framework that transfers the iterative VC editing model to SPLE. The tool allows to develop a software product line in a single-version workspace step by step, while variability management is completely automated. It offers familiar version control metaphors such as check-out and commit, and in addition uses the SPLE concepts of feature models and feature configuration the definition of logical variability and to define the logical scope of a change. SuperMod has been implemented in a model-driven way and primarily targets EMF models as software artifacts. We successfully apply the tool to a standard SPLE example.

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.

Software product line (SPL) engineering has emerged to become a mature domain for maximizing reuse within the context of a family of related software products. Within the process of SPL, the variability and commonality among the different products within the scope of a family is captured and modeled into a system's `feature model'. Currently, there are no architecture description languages (ADLs) that support the relationship between the feature model domain and the system architecture domain, leaving a gap which significantly increases the complexity of analyzing the system's architecture and insuring that it complies with its set feature model and variability requirements. In this paper we present ADLARS, an architecture description language that supports the relationship between the system's feature model and the architectural structures in an attempt to alleviate the aforementioned problem. The link between the two spaces also allows the automatic generation of product architectures from the family reference architecture

Towards Software Product Lines Optimization Using Evolutionary Algorithms

A software product line (SPL) usually involves a shared set of core assets and a series of application products. To ensure consistency, the evolution of the core assets and all the application products should be coordinated and synchronized under a unified evolution process. Therefore, SPL evolution often involves cross-product propagation and synchronization besides application derivation based on core assets, presenting quite different characteristic from the evolution of individual software products. As software architectures, including the product line architecture (PLA) and application architectures, play a central role in SPL engineering and evolution, architecture-based evolution analysis is a natural way for analyzing and managing SPL evolution. In this paper, we explore common practices of architecture evolution and the rationale behind in industrial SPL development. To this end, we conduct a case study with Wingsoft examination system product line (WES-PL), an industrial product line with an evolution history of eight years and more than 10 application products. In the case study, we reviewed the evolution history of WES-PL architecture and analyzed several typical evolution cases. Based on the historical analysis, we identify some special problems in industrial SPL practice from the aspect of architecture evolution and summarize some useful experiences about SPL evolution decisions to complement classical SPL methodology. On the other hand, we also propose some possible improvements for the evolution management in WES-PL.

Due to ever-evolving software developments processes, companies are motivated to develop desired quality products quickly and effectively. Industries are now focusing on the delivery of configurable systems to provide several services to a wide range of customers by making different configurations in a single largest system. Nowadays, component-based systems are highly demanded due to their capability of reusability and restructuring of existing components to develop new systems. Moreover, product line engineering is the major branch of the component-based system for developing a series of systems. Software product line engineering (SPLE) provides the ability to design several software modifications according to customer needs in a cost-effective manner. Researchers are trying to tailor the software product line (SPL) process that integrates agile development technologies to overcome the issues faced during the execution of the SPL process such as delay in product delivery, restriction to requirements change, and exhaustive initial planning. The selection of suitable components, the need for documentation, and tracing back the user requirements in the agile-integrated product line (APL) models still need to improve. Furthermore, configurable systems demand the selected features to be the least dependent. In this paper, a hybrid APL model, quality enhanced application product line engineering (QeAPLE) is proposed that provides support for highly configurable systems (HCS) by evaluating the dependency of features before making the final selection. It also has a documentation and requirement traceability function to ensure that the product meets the desired quality. Two-fold assessments are undertaken to validate the suggested model, with the proposed model being deployed on an active project. After that, we evaluated the proposed model performance and effectiveness using after implementing it in a real-world environment and compared the results with an existing method using statistical analysis. The results of the experimental study proofs that the proposed model is practically and statistically significant as compared to the existing method in terms of effectiveness and participants’ performance. Hence, the statistical results of the comparative analysis show that the proposed model improved ease of understanding and adaptability, required effort, high-quality achievement, and version management are significant i.e., more the 50% as compared to the exiting method i.e., less than 50%. The proposed model offers to assist in the development of a highly configurable system that achieves the needed quality. Therefore, the proposed model manages the variation identification, versions control, components dependency for correct selection of components, and validation activities from domain engineering to application engineering.

Design science research (DSR) aims to deliver innovative solutions for real-world problems. DSR produces Information Systems (IS) artifacts and design knowledge describing means-end relationships between problem and solution spaces. A key success factor of any DSR research endeavor is an appropriate understanding and description of the underlying problem space. However, existing DSR literature lacks a solid conceptualization of the problem space in DSR. This paper addresses this gap and suggests a conceptualization of the problem space in DSR that builds on the four key concepts of stakeholders, needs, goals, and requirements. We showcase the application of our conceptualization in two published DSR projects. Our work contributes methodologically to the field of DSR as it helps DSR scholars to explore and describe the problem space in terms of a set of key concepts and their relationships.

Product line software engineering (PLSE) is an emerging software engineering paradigm, which guides organizations toward the development of products from core assets rather than the development of products one by one from scratch. In order to develop highly reusable core assets, PLSE must have the ability to exploit commonality and manage variability among products from a domain perspective. Feature modeling is one of the most popular domain analysis techniques, which analyzes commonality and variability in a domain to develop highly reusable core assets for a product line. Various attempts have been made to extend and apply it to the development of software product lines. However, feature modeling can be difficult and time-consuming without a precise understanding of the goals of feature modeling and the aid of practical guidelines. In this paper, we clarify the concept of features and the goals of feature modeling, and provide practical guidelines for successful product line software engineering. The authors have extensively used feature modeling in several industrial product line projects and the guidelines described in this paper are based on these experiences.

Software product line engineering (SPLE) is a paradigm to promote systematic software reuse. A Feature Model (FM) is a common means to illustrate the commonality and variability of software products in a family. In most existing FM extraction approaches, keywords in the requirement document or certain types of system behavior or external events are considered features. The resulting FM is a combination of user activities and system actions (SAs), making it hard to understand. In this paper, we present an automatic approach to generate a product line FM from multiple requirement documents. We consider user activity and SAs separately in our approach and focus on the expected behaviors of the software system, together with the data being processed. The resulting FM clearly illustrates the expected functionalities of the software system and their variability in the product line. We also compared our approach with existing techniques by processing the same textual documents, and noted improvements in our results.

Adopting a software product line approach allows companies to realise significant improvements in time-to-market, cost, productivity, and system quality, A fundamental problem in software product line engineering is the fact that a product line of industrial size can easily incorporate several thousand variation points. The scale and interdependencies can lead to variability management and product derivation tasks that are extremely complex to manage. This paper investigates visualisation techniques to support and improve the effectiveness of these tasks.

In the machine learning based on kernel tricks, people often put one variable of a kernel function on the given samples to produce the basic functions of a solution space of learning problem. If the collection of the given samples deviates from the data distribution, the solution space spanned by these basic functions will also deviate from the real solution space of learning problem. In this paper a multikernel-like learning algorithm based on data probability distribution (MKDPD) is proposed, in which the parameters of a kernel function are locally adjusted according to the data probability distribution, and thus produces different kernel functions. These different kernel functions will generate different Reproducing Kernel Hilbert Spaces (RKHS). The direct sum of the subspaces of these RKHS constitutes the solution space of learning problem. Furthermore, based on the proposed MKDPD algorithm, a new algorithm for labeling new coming data is proposed, in which the basic functions are retrained according to the new coming data, while the coefficients of the retrained basic functions remained unchanged to label the new coming data. The experimental results presented in this paper show the effectiveness of the proposed algorithms.