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.     

基于构件的产品线方法在数控领域的应用

在复杂的大型数控软件系统的开发过程中，往往存在开发成本高、周期长、复用性差等特点。本文针对数控领域中的各个系统存在着大量的相似性和共同点，提出了一种面向整个数控领域的软件开发过程--基于构件的产品线方法．并提出了其产品线构架和核心资产库框架。由此实现数控领域中的大力度的软件复用、降低开发成本、缩短开发周期，并支持数控系统用户对产品的定制性要求。     

拉曼检测仪软件产品线的设计与应用

拉曼光谱技术在危险品检测、海关/边防查私、药品鉴定、文物真伪鉴定、矿物勘探、石油成分鉴定等领域有广泛应用,为了提高软件产品研发效率和质量、降低工作量,研究并设计了一种拉曼检测仪软件产品线。首先进行核心资源开发,在此基础上再开发具体的软件产品。通过对拉曼检测仪软件产品线的设计和应用,对软件产品线领域具体化作了一次有益尝试,为类似应用提供了可借鉴方案。     

软件产品线可变性建模技术系统综述

软件产品线是实现大规模的软件复用、保证高质量的新产品开发的最佳实践.软件产品线的关键问题是如何进行可变性管理,并基于可变性管理实现软件核心资产的复用.软件产品线可变性建模是可变性管理的关键技术,实现产品家族成员的共性和可变性的描述.可变性建模涉及软件开发的全生命周期,在领域工程和应用工程中,尤其是在产品构建过程中,起到重要的作用.从众多的建模技术中选择合适的建模技术是十分困难的,在软件产品线领域中开展了可变性建模技术的系统综述,按照系统综述的方法对可变性建模技术进行了系统总结,根据系统综述规则,选取了从1990 年~2011 年发表的论文进行综述.讨论了系统综述的研究成果,从可变性建模方法分类、重要可变性建模技术对比等方面进行深入的探讨,为建模人员和研究人员对可变性建模技术的选择和研究提供支持.最后分析了可变性建模技术的研究趋势,并对可变性建模技术有待深入的研究难点和发展趋势进行了展望.     

产品线工程理论应用与研究

产品线工程（Product Line Engineering）是运用软件重用思想的一种软件开发方法,它属于一种大粒度的软件复用方式,用于开发相同领域的类似产品过程。由于PLE强调针对特定产品集合的领域开发和面向重用技术,所以能有效地提高软件产品的开发效率和质量,降低软件开发成本。文中介绍了PLE理论,着重研究产品线模型、开发模式、生命周期和体系结构,介绍领域工程和应用工程在生命周期内部的交互作用。通过产品线开发周期分析和比较出PLE在系统开发过程中的特点,最后介绍PLE在HIS系统中的开发应用。     

一种基于特征迁移系统的软件产品线测试方法

为了在软件产品线的应用工程阶段最大程度地复用领域工程的测试用例,领域测试用例需要覆盖领域模型中的变化性.针对此问题,提出了一种以特征模型为出发点的软件产品线测试方法,通过扩展特征迁移系统建立软件产品线的领域行为模型,对模型中的变化性迁移进行抽象,得到精简的测试模型;应用迁移覆盖准则,导出包含变化性的领域测试用例;在应用工程阶段,根据具体应用所包含的特征,绑定领域测试用例中的变化性,复用领域测试用例导出针对具体应用的测试用例.最后通过一个咖啡机产品线验证了该测试方法,导出了可复用的领域测试用例.     

产品线工程理论应用与研究

产品线工程(Product Line Engineering)是运用软件重用思想的一种软件开发方法,它属于一种大粒度的软件复用方式,用于开发相同领域的类似产品过程.由于PLE强调针对特定产品集合的领域开发和面向重用技术,所以能有效地提高软件产品的开发效率和质量,降低软件开发成本.文中介绍了PLE理论,着重研究产品线模型、开发模式、生命周期和体系结构,介绍领域工程和应用工程在生命周期内部的交互作用.通过产品线开发周期分析和比较出PLE在系统开发过程中的特点,最后介绍PLE在HIS系统中的开发应用.     

面向领域的软件开发的研究

传统的面向应用的软件开发模式不能迅速响应用户的需求,提出了一种大规模生产软件产品的构架,通过开发面向特定领域的软件产品族,复用产品族中的公共资产库,采用定制机制的方法开发面向用户的应用程序。并结合一个具体的例子详细说明如何使用此方法开发电信领域的网管系统构架及具体应用系统。     

煤矿安全监控领域可变性模型

针对传统的软件开发方法每次开发同类系统时,很少能复用之前累积的开发经验,造成大量的重复性劳动的问题,提出了软件产品线开发方法,并将该方法应用于煤矿安全监控系统软件的开发中。在对煤矿安全监控系统产品线分析的基础上,针对监控系统的共性和变性特征,探讨了各特征之间的关系,使用基于特征的可变性建模方法构建了煤矿安全监控领域可变性模型。该模型可对监控系统的可变性进行有效管理,同时在特征依赖规则的指导下,可快速完成具体的可定制监控系统的需求特征分析,为后续煤矿安全监控领域可复用框架的实现奠定了基础。     

产品线可变性的需求方法研究

软件产品线领域需求记录了不同软件产品的共性和可变性。在现有需求过程框架下,对产品线需求获取方法与需求分析方法进行了研究,完善了产品线需求可变性的管控机制。以原子需求为视点,提出了利用需求场景获取产品线领域需求的方法;通过原子需求构建的产品需求矩阵与用例需求矩阵,分析得出需求资源的可变性关系;通过可变性关系的形式化描述,建立产品线可变性用例模型。     

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.     

An approach to developing domain requirements as a core asset based on commonality and variability analysis in a product line

The methodologies of product line engineering emphasize proactive reuse to construct high-quality products more quickly that are less costly. Requirements engineering for software product families differs significantly from requirements engineering for single software products. The requirements for a product line are written for the group of systems as a whole, with requirements for individual systems specified by a delta or an increment to the generic set. Therefore, it is necessary to identify and explicitly denote the regions of commonality and points of variation at the requirements level. In this paper, we suggest a method of producing requirements that will be a core asset in the product line. We describe a process for developing domain requirements where commonality and variability in a domain are explicitly considered. A CASE environment, named DREAM, for managing commonality and variability analysis of domain requirements is also described. We also describe a case study for an e-travel system domain where we found that our approach to developing domain requirements based on commonality and variability analysis helped to produce domain requirements as a core asset for product lines.     

XTraQue: traceability for product line systems

Product line engineering has been increasingly used to support the development and deployment of software systems that share a common set of features and are developed based on the reuse of core assets. The large number and heterogeneity of documents generated during the development of product line systems may cause difficulties to identify common and variable aspects among applications, and to reuse core assets that are available under the product line. In this paper, we present a traceability approach for product line systems. Traceability has been recognised as an important task in software system development. Traceability relations can improve the quality of the product being developed and reduce development time and cost. We present a rule-based approach to support automatic generation of traceability relations between feature-based object-oriented documents. We define a traceability reference model with nine different types of traceability relations for eight types of documents. The traceability rules used in our work are classified into two groups namely (a) direct rules, which support the creation of traceability relations that do not depend on the existence of other relations, and (b) indirect rules, which require the existence of previously generated relations. The documents are represented in XML and the rules are represented in an extension of XQuery. A prototype tool called XTraQue has been implemented. This tool, together with a mobile phone product line case study, has been used to demonstrate and evaluate our work in various experiments. The results of these experiments are encouraging and comparable with other approaches that support automatic generation of traceability relations. This work has been partially supported by Dhurakijpundit University, Thailand.     

Feature-Oriented Nonfunctional Requirement Analysis for Software Product Line

Domain analysis in software product line (SPL) development provides a basis for core assets design and implementation by a systematic and comprehensive commonality/variability analysis. In feature-oriented SPL methods, products of the domain analysis are domain feature models and corresponding feature decision models to facilitate application-oriented customization. As in requirement analysis for a single system, the domain analysis in the SPL development should consider both functional and nonfunctional domain requirements. However, the nonfunctional requirements (NFRs) are often neglected in the existing domain analysis methods. In this paper, we propose a context-based method of the NFR analysis for the SPL development. In the method, NFRs are materialized by connecting nonfunctional goals with real-world context, thus NFR elicitation and variability analysis can be performed by context analysis for the whole domain with the assistance of NFR templates and NFR graphs. After the variability analysis, our method integrates both functional and nonfunctional perspectives by incorporating the nonfunctional goals and operationalizations into an initial functional feature model. NFR-related constraints are also elicited and integrated. Finally, a decision model with both functional and nonfunctional perspectives is constructed to facilitate application-oriented feature model customization. A computer-aided grading system (CAGS) product line is employed to demonstrate the method throughout the paper. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60703092 and 90818009, the National High Technology Research and Development 863 Program of China under Grant No. 2007AA01Z125.     

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%.     

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.     

A model-driven traceability framework for software product lines

Software product line (SPL) engineering is a recent approach to software development where a set of software products are derived for a well defined target application domain, from a common set of core assets using analogous means of production (for instance, through Model Driven Engineering). Therefore, such family of products are built from reuse, instead of developed individually from scratch. SPL promise to lower the costs of development, increase the quality of software, give clients more flexibility and reduce time to market. These benefits come with a set of new problems and turn some older problems possibly more complex. One of these problems is traceability management. In the European AMPLE project we are creating a common traceability framework across the various activities of the SPL development. We identified four orthogonal traceability dimensions in SPL development, one of which is an extension of what is often considered as “traceability of variability”. This constitutes one of the two contributions of this paper. The second contribution is the specification of a metamodel for a repository of traceability links in the context of SPL and the implementation of a respective traceability framework. This framework enables fundamental traceability management operations, such as trace import and export, modification, query and visualization. The power of our framework is highlighted with an example scenario.     

Software product lines: a case study

A software product line is a family of products that share common features to meet the needs of a market area. Systematic processes have been developed to dramatically reduce the cost of a product line. Such product‐line engineering processes have proven practical and effective in industrial use, but are not widely understood. The Family‐Oriented Abstraction, Specification and Translation (FAST) process has been used successfully at Lucent Technologies in over 25 domains, providing productivity improvements of as much as four to one. In this paper, we show how to use FAST to document precisely the key abstractions in a domain, exploit design patterns in a generic product‐line architecture, generate documentation and Java code, and automate testing to reduce costs. The paper is based on a detailed case study covering all aspects from domain analysis through testing. Copyright © 2000 John Wiley & Sons, Ltd.     

A rule‐based approach to detect and prevent inconsistency in the domain‐engineering process

A medium‐sized domain‐engineering process can contain thousands of features that all have constraint dependency rules between them. Therefore, the validation of the content of domain‐engineering process is vital to produce high‐quality software products. However, it is not feasible to do this manually. This paper aims to improve the quality of the software products generated by the domain‐engineering process by ensuring the validity of the results of that process. We propose rules for two operations: inconsistency detection and inconsistency prevention. We introduce first‐order logic (FOL) rules to detect three types of inconsistency and prevent the direct inconsistency in the domain‐engineering process. Developing FOL rules to detect and prevent inconsistency in the domain‐engineering process directly without the need to the configuration process is our main contribution. We performed some experiments to test the scalability and applicability of our approach on domain‐engineered software product lines containing 1000 assets to 20000 assets. The results show that our approach is scalable and could be utilized to improve the domain‐engineering process.