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.     

Supporting multiple perspectives in feature-based configuration

Feature diagrams have become commonplace in software product line engineering as a means to document variability early in the life cycle. Over the years, their application has also been extended to assist stakeholders in the configuration of software products. However, existing feature-based configuration techniques offer little support for tailoring configuration views to the profiles of the various stakeholders. In this paper, we propose a lightweight, yet formal and flexible, mechanism to leverage multidimensional separation of concerns in feature-based configuration. We propose a technique to specify concerns in feature diagrams and to generate automatically concern-specific configuration views. Three alternative visualisations are proposed. Our contributions are motivated and illustrated through excerpts from a real web-based meeting management application which was also used for a preliminary evaluation. We also report on the progress made in the development of a tool supporting multi-view feature-based configuration.     

Decision support for the software product line domain engineering lifecycle

Software product line engineering is a paradigm that advocates the reusability of software engineering assets and the rapid development of new applications for a target domain. These objectives are achieved by capturing the commonalities and variabilities between the applications of the target domain and through the development of comprehensive and variability-covering feature models. The feature models developed within the software product line development process need to cover the relevant features and aspects of the target domain. In other words, the feature models should be elaborate representations of the feature space of that domain. Given that feature models, i.e., software product line feature models, are developed mostly by domain analysts by sifting through domain documentation, corporate records and transcribed interviews, the process is a cumbersome and error-prone one. In this paper, we propose a decision support platform that assists domain analysts throughout the domain engineering lifecycle by: (1) automatically performing natural language processing tasks over domain documents and identifying important information for the domain analysts such as the features and integrity constraints that exist in the domain documents; (2) providing a collaboration platform around the domain documents such that multiple domain analysts can collaborate with each other during the process using a Wiki; (3) formulating semantic links between domain terminology with external widely used ontologies such as WordNet in order to disambiguate the terms used in domain documents; and (4) developing traceability links between the unstructured information available in the domain documents and their formal counterparts within the formal feature model representations. Results obtained from our controlled experimentations show that the decision support platform is effective in increasing the performance of the domain analysts during the domain engineering lifecycle in terms of both the coverage and accuracy measures.     

The effects of visualization and interaction techniques on feature model configuration

A Software Product Line is a set of software systems of a domain, which share some common features but also have significant variability. A feature model is a variability modeling artifact which represents differences among software products with respect to 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 selecting features in the feature model (referred to as the configuration process) and by instantiating the reference model. However, feature model configuration can be a cumbersome task because: 1) feature models may consist of a large number of features, which are hard to comprehend and maintain; and 2) many factors including technical limitations, implementation costs, stakeholders’ requirements and expectations must be considered in the configuration process. Recognizing these issues, a significant amount of research efforts has been dedicated to different aspects of feature model configuration such as automating the configuration process. Several approaches have been proposed to alleviate the feature model configuration challenges through applying visualization and interaction techniques. However, there have been limited empirical insights available into the impact of visualization and interaction techniques on the feature model configuration process. In this paper, we present a set of visualization and interaction interventions for representing and configuring feature models, which are then empirically validated to measure the impact of the proposed interventions. An empirical study was conducted by following the principles of control experiments in software engineering and by applying the well-known software quality standard ISO 9126 to operationalize the variables investigated in the experiment. The results of the empirical study revealed that the employed visualization and interaction interventions significantly improved completion time of comprehension and changing of the feature model configuration. Additionally, according to results, the proposed interventions are easy-to-use and easy-to-learn for the participants.     

Mapping feature models onto domain models: ensuring consistency of configured domain models

We present an approach to model-driven software product line engineering which is based on feature models and domain models. A feature model describes both common and varying properties of the instances of a software product line. The domain model is composed of a structural model (package and class diagrams) and a behavioral model (story diagrams). Features are mapped onto the domain model by annotating elements of the domain model with features. An element of a domain model is specific to the features included in its feature annotation. An instance of the product line is defined by a set of selected features (a feature configuration). A configuration of the domain model is built by excluding all elements whose feature set is not included in the feature configuration. To ensure consistency of the configured domain model, we define constraints on the annotations of inter-dependent domain model elements. These constraints guarantee that a model element may be selected only when the model elements are also included on which it depends. Violations of dependency constraints may be removed automatically with the help of an error repair tool which propagates features to dependent model elements.     

Decision-making coordination and efficient reasoning techniques for feature-based configuration

Software Product Lines is a contemporary approach to software development that exploits the similarities and differences within a family of systems in a particular domain of interest in order to provide a common infrastructure for deriving members of this family in a timely fashion, with high-quality standards, and at lower costs.In Software Product Lines, feature-based product configuration is the process of selecting the desired features for a given software product from a repository of features called a feature model. This process is usually carried out collaboratively by people with distinct skills and interests called stakeholders. Collaboration benefits stakeholders by allowing them to directly intervene in the configuration process. However, collaboration also raises an important side effect, i.e., the need of stakeholders to cope with decision conflicts. Conflicts arise when decisions that are locally consistent cannot be applied globally because they violate one or more constraints in the feature model.Unfortunately, current product configuration systems are typically single-user-based in the sense that they do not provide means to coordinate concurrent decision-making on the feature model. As a consequence, configuration is carried out by a single person that is in charge of representing the interests of all stakeholders and managing decision conflicts on their own. This results in an error-prone and time-consuming process that requires past decisions to be revisited continuously either to correct misinterpreted stakeholder requirements or to handle decision conflicts. Yet another challenging issue related to configuration problems is the typically high computational cost of configuration algorithms. In fact, these algorithms frequently fall into the category of NP-hard and thus can become intractable in practice.In this paper, our goal is two-fold. First, we revisit our work on Collaborative Product Configuration (CPC) in which we proposed an approach to describe and validate collaborative configuration scenarios. We discuss how collaborative configuration can be described in terms of a workflow-like plan that safely guides stakeholders during the configuration process. Second, we propose a preliminary set of reasoning algorithms tailored to the feature modelling domain that can be used to provide automated support for product configuration. In addition, we compare empirically the performance of the proposed algorithms to that of a general-purpose solution. We hope that the insights provided in this paper will encourage other researchers to develop new algorithms in the near future.     

Specification and automated validation of staged reconfiguration processes for dynamic software product lines

Dynamic software product lines (DSPLs) propose elaborated design and implementation principles for engineering highly configurable runtime-adaptive systems in a sustainable and feature-oriented way. For this, DSPLs add to classical software product lines (SPL) the notions of (1) staged (pre-)configurations with dedicated binding times for each individual feature, and (2) continuous runtime reconfigurations of dynamic features throughout the entire product life cycle. Especially in the context of safety- and mission-critical systems, the design of reliable DSPLs requires capabilities for accurately specifying and validating arbitrary complex constraints among configuration parameters and/or respective reconfiguration options. Compared to classical SPL domain analysis which is usually based on Boolean constraint solving, DSPL validation, therefore, further requires capabilities for checking temporal properties of reconfiguration processes. In this article, we present a comprehensive approach for modeling and automatically verifying essential validity properties of staged reconfiguration processes with complex binding time constraints during DSPL domain engineering. The novel modeling concepts introduced are motivated by (re-)configuration constraints apparent in a real-world industrial case study from the automation engineering domain, which are not properly expressible and analyzable using state-of-the-art SPL domain modeling approaches. We present a prototypical tool implementation based on the model checker SPIN and present evaluation results obtained from our industrial case study, demonstrating the applicability of the approach.     

基于特征切片的软件产品线模型检测

特征模型是一种描述软件产品线中共性和可变性特征的通用形式。特征模型象征着所有可能的应用程序配置空间,是实现个性化产品定制的基础。随着软件产品线的规模和复杂程度的增加,如何有效支持以用户需求为基础以及根据特定需求和利益相关者的目标进行个性定制开发是亟待解决的实际问题。提出一种根据用户需求对特征模型进行切片,进一步结合三值逻辑对行为模型进行抽象,最后利用模型检测技术对软件产品线进行验证的方法。实验结果证实了该方法的有效性。     

Visualization of variability and configuration options

When designing, constructing, and maintaining diverse and variable software systems, a key challenge is the complexity of systems. A potential approach to tackle this challenge are techniques from variability management and product line engineering to handle the diversity and variability. A key asset in variability management is a variability model, which explicitly specifies the commonalities and variability of a system and the constraints between variants. However, handling variability and configurations remains a challenge due to the complexity on a cognitive level as human engineers reach their limits in identifying, understanding, and using all relevant details. In this paper we address this issue by providing concepts for interactive visual tool support for the configuration of systems with the help of feature models. We discuss relevant principles from the area of information visualization and their application to the domain of feature model configuration. We discuss techniques for interactive configuration support based on a reasoning engine, which, e.g., ensures the validity of configurations. We illustrate our findings by a concrete tool solution called S2T2 Configurator.     

A holistic approach to feature modeling for product line requirements engineering

Requirements engineering (RE) offers the means to discover, model, and manage the requirements of the products that comprise a product line, while software product line engineering (SPLE) offers the means of realizing the products’ requirements from a common base of software assets. In practice, however, RE and SPLE have proven to be less complementary than they should. While some RE techniques, particularly goal modeling, support the exploration of alternative solutions, the appropriate solution is typically conditional on context and a large product line may have many product-defining contexts. Thus, scalability and traceability through into product line features are key challenges for RE. Feature modeling, by contrast, has been widely accepted as a way of modeling commonality and variability of products of a product line that may be very complex. In this paper, we propose a goal-driven feature modeling approach that separates a feature space in terms of problem space and solution space features, and establish explicit mappings between them. This approach contributes to reducing the inherent complexity of a mixed-view feature model, deriving key engineering drivers for developing core assets of a product line, and facilitating the quality-based product configuration.     

Intelligent software product line configurations: A literature review

A software product line (SPL) is a set of industrial software-intensive systems for configuring similar software products in which personalized feature sets are configured by different business teams. The integration of these feature sets can generate inconsistencies that are typically resolved through manual deliberation. This is a time-consuming process and leads to a potential loss of business resources. Artificial intelligence (AI) techniques can provide the best solution to address this issue autonomously through more efficient configurations, lesser inconsistencies and optimized resources. This paper presents the first literature review of both research and industrial AI applications to SPL configuration issues. Our results reveal only 19 relevant research works which employ traditional AI techniques on small feature sets with no real-life testing or application in industry. We categorize these works in a typology by identifying 8 perspectives of SPL. We also show that only 2 standard industrial SPL tools employ AI in a limited way to resolve inconsistencies. To inject more interest and application in this domain, we motivate and present future research directions. Particularly, using real-world SPL data, we demonstrate how predictive analytics (a state of the art AI technique) can separately model inconsistent and consistent patterns, and then predict inconsistencies in advance to help SPL designers during the configuration of a product.     

Heuristic and exact algorithms for product configuration in software product lines

Software product line (SPL) is a set of software applications that share a common set of features satisfying the specific needs of a particular market segment. SPL engineering is a paradigm to develop software applications that commonly use a feature model to capture and document common and variable features, and their relationships. A big challenge is to derive one product among all possible products in the SPL, which satisfies the business and customer requirements. This task is known as product configuration. Although product configuration has been extensively investigated in the literature, customer's preferences are frequently neglected. In this paper, we propose a novel approach to configure a product that considers both qualitative and quantitative feature properties. We model the product configuration task as a combinatorial optimization problem, and heuristic and exact algorithms are proposed. As far as we are concerned, this proposal is the first work in the literature that considers feature properties in both leaf and nonleaf features. Computational experiments showed that the best of our heuristics found optimal solutions for all instances where those are known. For the instances where optimal solutions are not known, our heuristic outperformed the best solution obtained by a one‐hour run of the exact algorithm by up to 67.89%.     

Integrated Vehicle Configuration System—Connecting the domains of mass customization

Configuration design for mass customized vehicles necessitates the coordination of customer requirements, product characteristics, production processes, and logistics networks, in order to achieve rapid response to customer orders. Existing product configurators are mainly used as sales tools, and fail to account for the requirements of the entire customer order fulfillment process. In this regard, this paper proposes an Integrated Vehicle Configuration System (IVCS) to facilitate customer order processing based on information from multiple domains in a mass customization environment. An IVCS business model is proposed to incorporate the decision factors for configuration design related to different planning stages. The business model is supported by a comprehensive ontology framework, which enhances communications between different stakeholders involved in the order fulfillment process. The configuration approach is based on combinations of selective and generative rules and can be integrated with existing ERP systems. It also provides mechanisms to handle configuration rules that allow users to convert soft preferences into product specifications, bill-of-materials, and, furthermore, into logistics configurations. An example of a computerized configuration system showcases the process from customer engineering to design and production.     

Domain modeling as a basis for building a meshing tool software product line

Meshing tools are highly complex software for generating and managing geometrical discretizations. Due to their complexity, they have generally been developed by end users – physicists, forest engineers, mechanical engineers – with ad hoc methodologies and not by applying well established software engineering practices. Different meshing tools have been developed over the years, making them a good application domain for Software Product Lines (SPLs). This paper proposes building a domain model that captures the different domain characteristics such as features, goals, scenarios and a lexicon, and the relationships among them. The model is partly specified using a formal language. The domain model captures product commonalities and variabilities as well as the particular characteristics of different SPL products. The paper presents a rigorous process for building the domain model, where specific roles, activities and artifacts are identified. This process also clearly establishes consistency and completeness conditions. The usefulness of the model and the process are validated by using them to generate a software product line of Tree Stem Deformation (TSD) meshing tools. We also present Meshing Tool Generator, a software that follows the SPL approach for generating meshing tools belonging to the TSD SPL. We show how an end user can easily generate three different TSD meshing tools using Meshing Tool Generator.     

A business maturity model of software product line engineering

In the recent past, software product line engineering has become one of the most promising practices in software industry with the potential to substantially increase the software development productivity. Software product line engineering approach spans the dimensions of business, architecture, software engineering process and organization. The increasing popularity of software product line engineering in the software industry necessitates a process maturity evaluation methodology. Accordingly, this paper presents a business maturity model of software product line, which is a methodology to evaluate the current maturity of the business dimension of a software product line in an organization. This model examines the coordination between product line engineering and the business aspects of software product line. It evaluates the maturity of the business dimension of software product line as a function of how a set of business practices are aligned with product line engineering in an organization. Using the model presented in this paper, we conducted two case studies and reported the assessment results. This research contributes towards establishing a comprehensive and unified strategy for a process maturity evaluation of software product lines.     

A scoped approach to traceability management

Traceability is the ability to describe and follow the life of a software artifact and a means for modeling the relations between software artifacts in an explicit way. Traceability has been successfully applied in many software engineering communities and has recently been adopted to document the transition among requirements, architecture and implementation. We present an approach to customize traceability to the situation at hand. Instead of automating tracing, or representing all possible traces, we scope the traces to be maintained to the activities stakeholders must carry out. We define core traceability paths, consisting of essential traceability links required to support the activities. We illustrate the approach through two examples: product derivation in software product lines, and release planning in software process management. By using a running software product line example, we explain why the core traceability paths identified are needed when navigating from feature to structural models and from family to product level and backward between models used in software product derivation. A feasibility study in release planning carried out in an industrial setting further illustrates the use of core traceability paths during production and measures the increase in performance of the development processes supported by our approach. These examples show that our approach can be successfully used to support both product and process traceability in a pragmatic yet efficient way.     

基于特征可变性建模教学服务管理系统的研究与实现

可变性建模是软件产品线领域研究热点,现阶段的研究局限在需求阶段,缺乏完整的理论体系,从领域工程到应用工程缺乏详细的指导。针对这些问题,本文改进特征模型构建方法和流程,使其支持软件全生命周期,加强各模型的映射关系,增强流程可操作性,保障模型间的一致性。最后,得到需求阶段和设计阶段的可变性模型,并成功应用到教学服务管理系统二次开发中。通过构件开发和效率比较,验证本文改进方法作为软件复用分支理论是实际可行的,并且能够提高开发效率。     

软件生产线方法

与分析、设计和实现单个软件系统的传统软件工程方法不同 ,本文提出一种开发和维护系列软件系统的生产线方法 .该方法是一种领域特有的 ,以体系结构为中心的 ,过程驱动的 ,基于技术的系统化方法 .重点探讨方法论、生产线、工具和技术     

An organizational maturity model of software product line engineering

Software product line engineering is an inter-disciplinary concept. It spans the dimensions of business, architecture, process, and the organization. Some of the potential benefits of this approach include cost reduction, improvements in product quality and a decrease in product development time. The increasing popularity of software product line engineering in the software industry necessitates a process maturity evaluation methodology. Accordingly, this paper presents an organizational maturity model of software product line engineering for evaluating the maturity of organizational dimension. The model assumes that organizational theories, behavior, and management play a critical role in the institutionalization of software product line engineering within an organization. Assessment questionnaires and a rating methodology comprise the framework of this model. The objective and design of the questionnaires are to collect information about the software product line engineering process from the dual perspectives of organizational behavior and management. Furthermore, we conducted two case studies and reported the assessment results using the organizational maturity model presented in this paper.