Dynamic decision models for staged software product line configuration

Software product line engineering practices offer desirable characteristics such as rapid product development, reduced time-to-market, and more affordable development costs as a result of systematic representation of the variabilities of a domain of discourse that leads to methodical reuse of software assets. The development lifecycle of a product line consists of two main phases: domain engineering, which deals with the understanding and formally modeling of the target domain, and application engineering that is concerned with the configuration of a product line into one concrete product based on the preferences and requirements of the stakeholders. The work presented in this paper focuses on the application engineering phase and builds both the theoretical and technological tools to assist the stakeholders in (a) understanding the complex interactions of the features of a product line; (b) eliciting the utility of each feature for the stakeholders and hence exposing the stakeholders’ otherwise implicit preferences in a way that they can more easily make decisions; and (c) dynamically building a decision model through interaction with the stakeholders and by considering the structural characteristics of software product line feature models, which will guide the stakeholders through the product configuration process. Initial exploratory empirical experiments that we have performed show that our proposed approach for helping stakeholders understand their feature preferences and its associated staged feature model configuration process is able to positively impact the quality of the end results of the application engineering process within the context of the limited number of participants. In addition, it has been observed that the offered tooling support is able to ease the staged feature model configuration process.     

办公自动化软件产品线的研究与设计

软件产品线是一组具有可管理的公共特性的产品集合。选取网络办公自动化（OA）系统作为特定的研究领域，在分析此领域中产品的共性后，给出了OA系统软件产品线的实现方法。具体描述了OA系统产品线的需求工程，OA系统产品线核心资产的提取，并以科技项目管理系统为例说明了如何将核心资产应用到具体的产品开发中。     

一种面向特征的软件产品线非功能需求建模方法

分析传统非功能需求定义的不足,基于需求分析阶段的系统抽象—"需求模型"重新定义非功能需求,规范并简化功能需求与非功能需求之间的关系。扩展面向特征的软件产品线建模方法,在特征模型中显式地建模功能需求、非功能需求、非功能需求类型以及它们之间的相互关系,沿用传统特征模型中固有的变化性建模机制建模并管理非功能需求的变化性,显式地复用与非功能需求相关的建模知识和资产,为进一步研究定量评估产品线变体质量的新技术奠定基础。设计了一个基于多视图的特征建模方法,指导开发者在迭代的过程中建模非功能需求和功能需求,支持关注点分离和模型的复杂性管控。实现了工具原型并进行了实例验证。     

基于特征模型的软件产品线可变性建模方法

特征建模是软件产品线开发中的一项关键活动,对特征可变性和特征依赖的建模是特征模型中最重要的组成部分。阐述了特征模型的元模型,着重讨论了特征可变性建模过程,详细分析了特征可变性、特征之间关系、特征依赖类型的识别方法和使用特征依赖矩阵的表示方法。在此基础上,还通过一个库房监视系统应用软件的产品线可变性建模实例验证了该方法的有效性。     

从领域需求到产品线体系结构的映射——一种面向特征的方法

领域需求之间的依赖关系对软件产品线的体系结构有很大的影响,在已有的面向特征的管理产品线需求依赖的方法中很少有研究从需求到产品线体系结构的映射.基于一种特征依赖的分类方法,提出了从领域需求到特征,以及从特征到产品线体系结构的映射规则.通过这些映射规则,一致的需求通过映射得到一致的产品线核心资产,从而减少产品线中核心资产的不一致性并增加产品线的复用程度.用金融领域的现货交易产品线作为实例说明这个方法的实用性.     

Requirements engineering for software product lines: A systematic literature review

ContextSoftware product line engineering (SPLE) is a growing area showing promising results in research and practice. In order to foster its further development and acceptance in industry, it is necessary to assess the quality of the research so that proper evidence for adoption and validity are ensured. This holds in particular for requirements engineering (RE) within SPLE, where a growing number of approaches have been proposed.ObjectiveThis paper focuses on RE within SPLE and has the following goals: assess research quality, synthesize evidence to suggest important implications for practice, and identify research trends, open problems, and areas for improvement.MethodA systematic literature review was conducted with three research questions and assessed 49 studies, dated from 1990 to 2009.ResultsThe evidence for adoption of the methods is not mature, given the primary focus on toy examples. The proposed approaches still have serious limitations in terms of rigor, credibility, and validity of their findings. Additionally, most approaches still lack tool support addressing the heterogeneity and mostly textual nature of requirements formats as well as address only the proactive SPLE adoption strategy.ConclusionsFurther empirical studies should be performed with sufficient rigor to enhance the body of evidence in RE within SPLE. In this context, there is a clear need for conducting studies comparing alternative methods. In order to address scalability and popularization of the approaches, future research should be invested in tool support and in addressing combined SPLE adoption strategies.     

面向软件动态演化的需求建模及其模型规范化

针对目前需求工程阶段对软件动态演化考虑不足的现状,在分析软件动态演化面临的挑战的基础上,设计了面向动态演化的需求元模型(dynamic-evolution-orientedrequi rements meta-model,DERM)。该元模型以特征为基本部件,按特征组合的方式建立需求模型,需求模型由行为特征和属性特征组成。行为特征被区分为计算行为特征和交互行为特征,以实现计算和交互的相对隔离;属性特征通过其作用域,指定其在行为特征模型中的作用范围,从而将行为特征模型和属性特征模型统一为需求模型。在此基础上,讨论了需求模型的参照完整性、依赖一致性和互斥一致性,并进一步把需求模型规范化为需求模型第一范式到第三范式,需求模型规范化的过程提供了一种保证需求模型一致性的方法。最后通过案例研究,表明了该方法的可行性及其对软件动态演化的有效支持。     

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.     

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%.     

Managing requirements inter-dependency for software product line derivation

Software Product Line Engineering (SPLE) can reduce software development costs, reduce time to market and improve product quality. A software product line is a set of software products sharing a set of common features but containing variation points. Successful SPLE requires making selection decisions at variation points effectively and efficiently. A significant challenge is how to identify, represent and manage the inter-dependency of selection decisions for requirements. We developed the concept of a meta-model for requirement decision models to bring formalism and consistency to the structure and to model inter-dependencies between requirement selection decisions. Here we present a meta-model for requirement selection decisions that includes inter-dependencies and we use a mobile phone worked example to illustrate our approach. To support our method, we developed two separate tools, V-Define (for domain decision model construction) and V-Resolve (for new product derivation). Finally the results of a metal processing product line case study using the tools are described.

ERP requirements engineering practice: lessons learned

Standard off-the-shelf requirements engineering processes have become a key to conceptualizing any integrated, corporate-wide solution based on packaged enterprise resource planning software. A generic RE model offers defined processes, suggests process stakeholders, specifies steps to accomplish tasks, indicates task dependencies, and provides standard tool support for ERP RE. Essentially, any off-the-shelf RE process is about composition and reconciliation: you start with a general set of business process and data requirements, then explore standard ERP functionality to see how closely it matches your organization's process and data needs.     

Requirements engineering in software product line engineering

Many attempts have been made to increase the productivity and quality of software products based on software reuse. Software product line practice is one such approach, one that focuses on developing a family of products which have a majority of features in common. Hence, there are numerous requirements that are common across the family, but others are unique to individual products. Traditional requirements engineering methods were conceived to deal with single product requirements and are usually not flexible enough to address the needs arising from reusing requirements for a family of products. There is also the additional burden of correctly identifying and engineering both product-line-wide requirements and product-specific requirements as well as evolving them. Therefore, in this special issue, we want to highlight the importance and the role of requirements engineering for product line development as well as to provide insights into the state of the art in the field.     

Scalable prediction of non-functional properties in software product lines: Footprint and memory consumption

ContextA software product line is a family of related software products, typically created from a set of common assets. Users select features to derive a product that fulfills their needs. Users often expect a product to have specific non-functional properties, such as a small footprint or a bounded response time. Because a product line may have an exponential number of products with respect to its features, it is usually not feasible to generate and measure non-functional properties for each possible product.ObjectiveOur overall goal is to derive optimal products with respect to non-functional requirements by showing customers which features must be selected.MethodWe propose an approach to predict a product’s non-functional properties based on the product’s feature selection. We aggregate the influence of each selected feature on a non-functional property to predict a product’s properties. We generate and measure a small set of products and, by comparing measurements, we approximate each feature’s influence on the non-functional property in question. As a research method, we conducted controlled experiments and evaluated prediction accuracy for the non-functional properties footprint and main-memory consumption. But, in principle, our approach is applicable for all quantifiable non-functional properties.ResultsWith nine software product lines, we demonstrate that our approach predicts the footprint with an average accuracy of 94%, and an accuracy of over 99% on average if feature interactions are known. In a further series of experiments, we predicted main memory consumption of six customizable programs and achieved an accuracy of 89% on average.ConclusionOur experiments suggest that, with only few measurements, it is possible to accurately predict non-functional properties of products of a product line. Furthermore, we show how already little domain knowledge can improve predictions and discuss trade-offs between accuracy and required number of measurements. With this technique, we provide a basis for many reasoning and product-derivation approaches.     

一种面向产品线的特征依赖建模方法

特征依赖建模是描述特征间相互约束的模型,是软件产品线开发中的一项关键活动。引入了特征局部依赖和全局依赖关系,在对特征依赖关系分析的基础上,提出了一种特征依赖建模方法,该方法不仅支持分解、泛化等特征局部依赖描述,还支持配置依赖、运行依赖和影响依赖等全局依赖建模。通过一个空调控制系统的产品线特征依赖建模实例验证了该方法的有效性。     

Testing variability-intensive systems using automated analysis: an application to Android

Software product lines are used to develop a set of software products that, while being different, share a common set of features. Feature models are used as a compact representation of all the products (e.g., possible configurations) of the product line. The number of products that a feature model encodes may grow exponentially with the number of features. This increases the cost of testing the products within a product line. Some proposals deal with this problem by reducing the testing space using different techniques. However, a daunting challenge is to explore how the cost and value of test cases can be modeled and optimized in order to have lower-cost testing processes. In this paper, we present TESting vAriAbiLity Intensive Systems (TESALIA), an approach that uses automated analysis of feature models to optimize the testing of variability-intensive systems. We model test value and cost as feature attributes, and then we use a constraint satisfaction solver to prune, prioritize and package product line tests complementing prior work in the software product line testing literature. A prototype implementation of TESALIA is used for validation in an Android example showing the benefits of maximizing the mobile market share (the value function) while meeting a budgetary constraint.     

基于特征分解模式的软件产品线参考设计方法

基于特征的领域分析与建模技术是软件产品线开发中较为主流的需求建模方法,为描述产品线共性和可变性及其之间的关系提供了良好的支持。然而在现有特征模型基础上,如何指导系统开发人员进行软件系统的详细设计是亟待解决的问题。该问题主要体现在特征之间的结构与语义关系,以及特征的可变性如何映射为合理的系统设计模型这两个方面。针对上述问题,提出一种基于特征分解模式的软件产品线参考设计方法。该方法为特征模型中具有不同结构、不同语义的特征分解模式提供参考的详细设计方案,并提出相关聚类准则以支持对应全局特征模型的设计模型优化。最后,通过成绩录入软件产品线对该方法的有效性进行验证。     

Combining service-orientation and software product line engineering: A systematic mapping study

ContextService-Orientation (SO) is a rapidly emerging paradigm for the design and development of adaptive and dynamic software systems. Software Product Line Engineering (SPLE) has also gained attention as a promising and successful software reuse development paradigm over the last decade and proven to provide effective solutions to deal with managing the growing complexity of software systems.ObjectiveThis study aims at characterizing and identifying the existing research on employing and leveraging SO and SPLE.MethodWe conducted a systematic mapping study to identify and analyze related literature. We identified 81 primary studies, dated from 2000–2011 and classified them with respect to research focus, types of research and contribution.ResultThe mapping synthesizes the available evidence about combining the synergy points and integration of SO and SPLE. The analysis shows that the majority of studies focus on service variability modeling and adaptive systems by employing SPLE principles and approaches.In particular, SPLE approaches, especially feature-oriented approaches for variability modeling, have been applied to the design and development of service-oriented systems. While SO is employed in software product line contexts for the realization of product lines to reconcile the flexibility, scalability and dynamism in product derivations thereby creating dynamic software product lines.ConclusionOur study summarizes and characterizes the SO and SPLE topics researchers have investigated over the past decade and identifies promising research directions as due to the synergy generated by integrating methods and techniques from these two areas.     

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.     

Quality attribute modeling and quality aware product configuration in software product lines

In software product line engineering, the customers mostly concentrate on the functionalities of the target product during product configuration. The quality attributes of a target product, such as security and performance, are often assessed until the final product is generated. However, it might be very costly to fix the problem if it is found that the generated product cannot satisfy the customers’ quality requirements. Although the quality of a generated product will be affected by all the life cycles of product development, feature-based product configuration is the first stage where the estimation or prediction of the quality attributes should be considered. As we know, the key issue of predicting the quality attributes for a product configured from feature models is to measure the interdependencies between functional features and quality attributes. The current existing approaches have several limitations on this issue, such as requiring real products for the measurement or involving domain experts’ efforts. To overcome these limitations, we propose a systematic approach of modeling quality attributes in feature models based on domain experts’ judgments using the analytic hierarchical process (AHP) and conducting quality aware product configuration based on the captured quality knowledge. Domain experts’ judgments are adapted to avoid generating the real products for quality evaluation, and AHP is used to reduce domain experts’ efforts involved in the judgments. A prototype tool is developed to implement the concepts of the proposed approach, and a formal evaluation is carried out based on a large-scale case study.     

MOD2-SCM: A model-driven product line for software configuration management systems

ContextSoftware Configuration Management (SCM) is the discipline of controlling the evolution of large and complex software systems. Over the years many different SCM systems sharing similar concepts have been implemented from scratch. Since these concepts usually are hard-wired into the respective program code, reuse is hardly possible.ObjectiveOur objective is to create a model-driven product line for SCM systems. By explicitly describing the different concepts using models, reuse can be performed on the modeling level. Since models are executable, the need for manual programming is eliminated. Furthermore, by providing a library of loosely coupled modules, we intend to support flexible composition of SCM systems.MethodWe developed a method and a tool set for model-driven software product line engineering which we applied to the SCM domain. For domain analysis, we applied the FORM method, resulting in a layered feature model for SCM systems. Furthermore, we developed an executable object-oriented domain model which was annotated with features from the feature model. A specific SCM system is configured by selecting features from the feature model and elements of the domain model realizing these features.ResultsDue to the orthogonality of both feature model and domain model, a very large number of SCM systems may be configured. We tested our approach by creating instances of the product line which mimic wide-spread systems such as CVS, GIT, Mercurial, and Subversion.ConclusionThe experiences gained from this project demonstrate the feasibility of our approach to model-driven software product line engineering. Furthermore, our work advances the state of the art in the domain of SCM systems since it support the modular composition of SCM systems at the model rather than the code level.