Evaluation of Frame- and Feature-based Software Product Line Tools from the Viewpoint of Mass Customization by End Users

Customers expect Information and Communications Technology (ICT) platforms and applications to deliver services customized to their needs. Software product line (SPL) paradigm uses platforms and variability management to develop mass-customizable software applications. The paradigm necessitates effective software tools to manage platform and application artifacts and traceability and variability information. This paper constructs a comprehensive but lightweight tool evaluation framework and uses it to evaluate two tools, XML-based variant configuration language (XVCL) and FeaturePlugin – a feature modeling plug-in for Eclipse Integrated Development Environment. The paper analyzes the capabilities of the tools for enabling the mass customization of software applications by the end users performing complex workflows. Both the XVCL and FeaturePlugin tool envisage more efficient software system development by means of reusability, support for abstraction, and configuration mechanisms. Future research is needed to refine and validate the evaluation framework in the context of other types of SPL tools

RED-PL, a Method for Deriving Product Requirements from a Product Line Requirements Model

International audienceSoftware product lines (SPL) modeling has proven to be an effective approach to reuse in software development. Several variability approaches were developed to plan requirements reuse, but only little of them actually address the issue of deriving product requirements. Indeed, while the modeling approaches sell on requirements reuse, the associated derivation techniques actually focus on deriving and reusing technical product data.This paper presents a method that intends to support requirements derivation.Its underlying principle is to take advantage of approaches made for reuse PL requirements and to complete them by a requirements development process by reuse for single products. The proposed approach matches users' product requirements with PL requirements models and derives a collection ofrequirements that is (i) consistent, and (ii) optimal with respect to users' priorities and company's constraints. The proposed methodological process was validated in an industrial setting by considering the requirement engineering phase of a product line of blood analyzers

Deriving Product Line Requirements: the RED-PL Guidance Approach

Product lines (PL) modeling have proven to be an effective approach to reuse in software development.Several variability approaches were developed to plan requirements reuse, but only little of them actuallyaddress the issue of deriving product requirements.This paper presents a method, RED-PL that intends to support requirements derivation. The originality ofthe proposed approach is that (i) it is user-oriented, (ii) it guides product requirements elicitation andderivation as a decision making activity, and (iii) it provides systematic and interactive guidance assistinganalysts in taking decisions about requirements. The RED-PL methodological process was validatedin an industrial setting by considering the requirement engineering phase of a product line of blood analyzers

A Feature-Oriented Approach to Developing Dynamically Reconfigurable Products in Product Line Engineering

Dynamic product reconfiguration refers to making changes to a deployed product configuration while a system is running. Recently, there have been increasing demands for dynamic product reconfiguration in various application areas (e.g., ubiquitous computing, self-healing systems, etc.); however, most product line engineering methods in the literature have focused on the development of reusable core assets for statically configured products. In this paper, we propose a feature-oriented approach to develop dynamically reconfigurable core assets. This approach takes feature binding analysis results as a key design driver for identifying and managing variation points of dynamically reconfigurable products. We also provide a conceptual model for a reconfigurator, which monitors and manages product reconfiguration at run time. The method is illustrated with a home service robot product line exampl

A Feature-Oriented Approach to Developing Dynamically Reconfigurable Products in Product Line Engineering

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A survey on engineering approaches for self-adaptive systems (extended version)

The complexity of information systems is increasing in recent years, leading to increased effort for maintenance and configuration. Self-adaptive systems (SASs) address this issue. Due to new computing trends, such as pervasive computing, miniaturization of IT leads to mobile devices with the emerging need for context adaptation. Therefore, it is beneficial that devices are able to adapt context. Hence, we propose to extend the definition of SASs and include context adaptation. This paper presents a taxonomy of self-adaptation and a survey on engineering SASs. Based on the taxonomy and the survey, we motivate a new perspective on SAS including context adaptation

Applying Software Product Lines to Build Autonomic Pervasive Systems

In this Master Thesis, we have proposed a model-driven Software Product Line (SPL) for developing autonomic pervasive systems. The work focusses on reusing the Variability knowledge from the SPL design to the SPL products. This Variability knowledge enables SPL products to deal with adaptation scenarios (evolution and involution) in an autonomic way.Cetina Englada, C. (2008). Applying Software Product Lines to Build Autonomic Pervasive Systems. http://hdl.handle.net/10251/12447Archivo delegad

Variability-Modelling Practices in Industrial Software Product Lines: A Qualitative Study

Many organizations have transitioned from single-systems development to product-line development with the goal of increasing productivity and facilitating mass customization. Variability modelling is a key activity in software product-line development that deals with the explicit representation of variability using dedicated models. Variability models specify points of variability and their variants in a product line. Although many variability-modelling notations and tools have been designed by researchers and practitioners, very little is known about their usage, actual benefits or challenges. Existing studies mostly describe product-line practices in general, with little focus on variability modelling. We address this gap through a qualitative study on variability-modelling practices in medium- and large-scale companies using two empirical methods: surveys and interviews. We investigated companies' variability-modelling practices and experiences with the aim to gather information on 1) the methods and strategies used to create and manage variability models, 2) the tools and notations used for variability modelling, 3) the perceived values and challenges of variability modelling, and 4) the core characteristics of their variability models. Our results show that variability models are often created by re-engineering existing products into a product line. All of the interviewees and the majority of survey participants indicated that they represent variability using separate variability models rather than annotative approaches. We found that developers use variability models for many purposes, such as the visualization of variabilities, configuration of products, and scoping of products. Although we observed that high degree of heterogeneity exists in the variability-modelling notations and tools used by organizations, feature-based notations and tools are the most common. We saw huge differences in the sizes of variability models and their contents, which indicate that variability models can have different use cases depending on the organization. Most of our study participants reported complexity challenges that were related mainly to the visualization and evolution of variability models, and dependency management. In addition, reports from interviews suggest that product-line adoption and variability modelling have forced developers to think in terms of a product-line scenario rather than a product-based scenario

Run-time Variability with Roles

Adaptability is an intrinsic property of software systems that require adaptation to cope with dynamically changing environments. Achieving adaptability is challenging. Variability is a key solution as it enables a software system to change its behavior which corresponds to a specific need. The abstraction of variability is to manage variants, which are dynamic parts to be composed to the base system. Run-time variability realizes these variant compositions dynamically at run time to enable adaptation. Adaptation, relying on variants specified at build time, is called anticipated adaptation, which allows the system behavior to change with respect to a set of predefined execution environments. This implies the inability to solve practical problems in which the execution environment is not completely fixed and often unknown until run time. Enabling unanticipated adaptation, which allows variants to be dynamically added at run time, alleviates this inability, but it holds several implications yielding system instability such as inconsistency and run-time failures. Adaptation should be performed only when a system reaches a consistent state to avoid inconsistency. Inconsistency is an effect of adaptation happening when the system changes the state and behavior while a series of methods is still invoking. A software bug is another source of system instability. It often appears in a variant composition and is brought to the system during adaptation. The problem is even more critical for unanticipated adaptation as the system has no prior knowledge of the new variants. This dissertation aims to achieve anticipated and unanticipated adaptation. In achieving adaptation, the issues of inconsistency and software failures, which may happen as a consequence of run-time adaptation, are evidently addressed as well. Roles encapsulate dynamic behavior used to adapt players representing the base system, which is the rationale to select roles as the software system's variants. Based on the role concept, this dissertation presents three mechanisms to comprehensively address adaptation. First, a dynamic instance binding mechanism is proposed to loosely bind players and roles. Dynamic binding of roles enables anticipated and unanticipated adaptation. Second, an object-level tranquility mechanism is proposed to avoid inconsistency by allowing a player object to adapt only when its consistent state is reached. Last, a rollback recovery mechanism is proposed as a proactive mechanism to embrace and handle failures resulting from a defective composition of variants. A checkpoint of a system configuration is created before adaptation. If a specialized bug sensor detects a failure, the system rolls back to the most recent checkpoint. These mechanisms are integrated into a role-based runtime, called LyRT. LyRT was validated with three case studies to demonstrate the practical feasibility. This validation showed that LyRT is more advanced than the existing variability approaches with respect to adaptation due to its consistency control and failure handling. Besides, several benchmarks were set up to quantify the overhead of LyRT concerning the execution time of adaptation. The results revealed that the overhead introduced to achieve anticipated and unanticipated adaptation to be small enough for practical use in adaptive software systems. Thus, LyRT is suitable for adaptive software systems that frequently require the adaptation of large sets of objects

Achieving Autonomic Computing through the Use of Variability Models at Run-time

Increasingly, software needs to dynamically adapt its behavior at run-time in response to changing conditions in the supporting computing infrastructure and in the surrounding physical environment. Adaptability is emerging as a necessary underlying capability, particularly for highly dynamic systems such as context-aware or ubiquitous systems. By automating tasks such as installation, adaptation, or healing, Autonomic Computing envisions computing environments that evolve without the need for human intervention. Even though there is a fair amount of work on architectures and their theoretical design, Autonomic Computing was criticised as being a \hype topic" because very little of it has been implemented fully. Furthermore, given that the autonomic system must change states at runtime and that some of those states may emerge and are much less deterministic, there is a great challenge to provide new guidelines, techniques and tools to help autonomic system development. This thesis shows that building up on the central ideas of Model Driven Development (Models as rst-order citizens) and Software Product Lines (Variability Management) can play a signi cant role as we move towards implementing the key self-management properties associated with autonomic computing. The presented approach encompass systems that are capable of modifying their own behavior with respect to changes in their operating environment, by using variability models as if they were the policies that drive the system's autonomic recon guration at runtime. Under a set of recon guration commands, the components that make up the architecture dynamically cooperate to change the con guration of the architecture to a new con guration. This work also provides the implementation of a Model-Based Recon guration Engine (MoRE) to blend the above ideas. Given a context event, MoRE queries the variability models to determine how the system should evolve, and then it provides the mechanisms for modifying the system.Cetina Englada, C. (2010). Achieving Autonomic Computing through the Use of Variability Models at Run-time [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7484Palanci