Structuring the modeling space and supporting evolution in software product line engineering

The scale and complexity of product lines means that it is practically infeasible to develop a single model of the entire system, regardless of the languages or notations used. The dynamic nature of real-world systems means that product line models need to evolve continuously to meet new customer requirements and to reflect changes of product line artifacts. To address these challenges, product line engineers need to apply different strategies for structuring the modeling space to ease the creation and maintenance of models. This paper presents an approach that aims at reducing the maintenance effort by organizing product lines as a set of interrelated model fragments defining the variability of particular parts of the system. We provide support to semi-automatically merge fragments into complete product line models. We also provide support to automatically detect inconsistencies between product line artifacts and the models representing these artifacts after changes. Furthermore, our approach supports the co-evolution of models and their respective meta-models. We discuss strategies for structuring the modeling space and show the usefulness of our approach using real-world examples from our ongoing industry collaboration.     

Constraint programming for type inference in flexible model-driven engineering

Domain experts typically have detailed knowledge of the concepts that are used in their domain; however they often lack the technical skills needed to translate that knowledge into model-driven engineering (MDE) idioms and technologies. Flexible or bottom-up modelling has been introduced to assist with the involvement of domain experts by promoting the use of simple drawing tools. In traditional MDE the engineering process starts with the definition of a metamodel which is used for the instantiation of models. In bottom-up MDE example models are defined at the beginning, letting the domain experts and language engineers focus on expressing the concepts rather than spending time on technical details of the metamodelling infrastructure. The metamodel is then created manually or inferred automatically. The flexibility that bottom-up MDE offers comes with the cost of having nodes in the example models left untyped. As a result, concepts that might be important for the definition of the domain will be ignored while the example models cannot be adequately re-used in future iterations of the language definition process. In this paper, we propose a novel approach that assists in the inference of the types of untyped model elements using Constraint Programming. We evaluate the proposed approach in a number of example models to identify the performance of the prediction mechanism and the benefits it offers. The reduction in the effort needed to complete the missing types reaches up to 91.45% compared to the scenario where the language engineers had to identify and complete the types without guidance.     

企业时态化建模中的元模型研究

为了支持企业历史信息等与时间特征相关的建模，提出了包括日历对象、时间属性域类型、时间戳等在内的基本元模型。利用这些基本元模型，建模者可以在现有企业模型的基础上实现基于时间特征的时态化扩展建模，从而提高企业模型及其应用系统的弹性。     

Concern coverage in base station development: an empirical investigation

Contemporary model driven development tools only partially support the abstractions occurring in complex embedded systems development. This article presents an interpretive case study in which architectural concerns important to seven engineers in a large product developing organization were compared to the views actually provided by the organization??s models. The paper??s main finding is an empirically grounded catalogue of architectural concerns for a large, complex embedded systems project, and an assessment of the degree to which the studied organization has managed to realize support for these concerns within economical and organizational constraints. In the studied case, 114 different architectural concerns were found to be important to the interviewed engineers. Of this sample, 75% were documented in models, structured text, or informal documentation, whereas 47% of all documented concerns were modeled. The paper??s conclusion is that current modeling languages and methods inadequately address the full set of concerns that are important to engineers in base station development.     

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.     

Evidence-driven decision support in critical infrastructure management through enhanced domain knowledge modeling

Effective critical infrastructure management in dynamically changing service environments requires understanding and inferring unknown knowledge from complex heterogeneous dataset to reason about multi-dimensional complex problem solving activities by aggregating supporting evidences. While the attributes of the database table only describe data and certain notions from the database relational schema, they do not describe the higher-level concepts or the knowledge from the domain that are commonly thought of and referred by engineers who need to inspect and manage the infrastructure with a holistic viewpoint. Thus, engineers have to work with rudimentary data-level attributes that, further, complicates the critical infrastructure management, which essentially needs efficient, effective, and informed decision making. Ontology enables to solve a complex problem where the underlying domain concept provides collective understanding of the data based on the domain knowledge from multi-dimensional resources. Enhanced domain knowledge modeling is applied for transportation infrastructure asset management that requires bridge inspectors to make decisions based on complex multi-layered heterogeneous data, such as, infrared image data, aerial photo data, ground-mounted LIDAR data, etc. The ontological concepts represent the process knowledge and assessment knowledge and it will be further used to support the bridge inspectors and their inspection process, whereas data are the ground facts. This process knowledge plays an important role to bridge the ground facts and the high-level concept space and provides the mapping of the complex data space to the easily comprehensible conceptual space. In making critical decisions, these become crucial evidences in justifying decisions made as well as in making uniform decisions among different subject matter experts through the common understanding.     

语义驱动的集成化产品建模

针对复杂产品研发过程中多领域协同对产品知识共享和重用的需求,提出一种语义驱动的集成化产品建模方法.结合多本体技术,给出了集成化产品建模框架,该框架由概念层和模型层构成,概念层包括高层核心产品本体和领域本体,模型层由主模型和领域模型等一族模型构成;同时还给出了集成化产品模型的形式化语义描述,在构建高层核心产品本体的基础上建立主模型;基于多领域本体,进行由概念层语义驱动的领域模型快速重构,在语义理解基础上实现跨领域的产品知识重用.     

A knowledge-based prototyping environment for construction of scientific modeling software

Over the past 30 years, scientific software models have played an increasingly prominent role in the conduct of science. Unfortunately, scientific models can be difficult and time-consuming to implement, and there is little software engineering support specifically available for constructing scientific models. Because these models are not easily specified to scientifically-naive programmers, and because the scientist requires intimate knowledge of the code to conduct experiments, many scientists implement their own models. This coding activity takes valuable time away from their primary scientific mission. We have developed a knowledge-based software development tool that assists scientists in prototyping scientific models. With a specialized graphical user interface, the scientist constructs a high-level visual specification that captures the essential computational dependencies in the desired model. The system uses its scientific domain knowledge to ensure that the model being built is consistent and coherent. The final product is an executable prototype of a scientific model. Our tool accelerates the model-building process and eliminates the scientist's need to program in a formal language. Furthermore, the models developed with this tool are easier to understand and reuse than typical low-level scientific modeling code. At present, models developed with our system are restricted to those involving non-coupled algebraic and first order ordinary differential equations. Research is ongoing to lessen this restriction and support models with simultaneous equations.     

Using a trope-based foundational ontology for bridging different areas of concern in ontology-driven conceptual modeling

In recent years, ontology-driven reference models have gained much attention in the literature due to their potential key role in activities such as complex information modeling and semantic interoperability. The engineering process of these conceptual models should account for different phases addressing different areas of concern. In an initial phase of conceptual domain modeling, the target modeling artifacts should be constructed with the goal of maximizing quality attributes such as expressivity and truthfulness to the represented domain in reality. In a subsequent development phase, the resulting domain models can be used to guide the design decisions in the construction of different implementation artifacts addressing different computational concerns. In this paper, we present a philosophically sound, cognitively-oriented and formally characterized foundational theory of objects and tropes (property-instances). Moreover, we use this theory to bring about engineering contributions to both the aforementioned phases of ontology-driven conceptual modeling. Firstly, we show how this theory has been used to (re)design a system of modeling primitives underlying the conceptual domain modeling language OntoUML. Furthermore, we provide precise directives on how to map conceptual domain models in this language to their implementation in less-expressive computationally-oriented codification languages. In particular, we address here a mapping strategy to OWL (Web Ontology Language) that partially preserves the modal-temporal semantics of OntoUML. Finally, we discuss computational support for the proposed approach in terms of conceptual model construction, automatic transformation and temporal querying.     

基于模糊UML的装备保障知识建模方法

装备保障业务需求建模是装备保障信息系统研发的重要环节,准确描述业务概念和关系是获取高质量需求分析产品的重要前提。然而,该业务领域中用户目标、业务效果等核心要素常包含模糊或不确定信息,容易引发系统研发各方的需求理解偏差,从而给系统后期的设计、开发带来巨大隐患。针对上述问题,首先从装备保障领域知识建模出发,挖掘本领域核心知识,构成装备保障领域知识本体,在此基础上借助UML建模语言MOF层扩展机制,引入模糊评估属性和建模元素,进而形成一种可用于该领域信息系统业务建模分析的领域特定建模语言。该建模语言对领域内存在的明确和模糊需求信息同样具有良好的表达能力,便于系统研发各方在信息系统需求分析阶段达成共识,进而为准确捕捉装备保障业务需求提供技术支持。     

基于本体的军事装备知识建模及分析

针对本体建模过程中不同受众具有不同应用需求的问题,结合本体建模七步法和软件开发螺旋模型提出基于需求的螺旋反馈法。首先,明确领域知识范畴和用户需求,进行本体总体设计;其次,领域专家依据本体构建原则评估知识体系;再次,组装知识体系模型,定义本体属性,创建实例,完成本体详细设计;最后,用户评估反馈,进行新一轮的增量迭代,直至形成正确可用的知识体系。与七步法相比,所提方法强调本体测试和用户需求,以小的分段来构建领域知识模型。此外,运用该方法实现的军事装备知识体系面向作战需求,为军事作战提供强有力的理论支撑。     

Building Linear Programming Models from Structural Model Components

Model management research investigates the formulation, analysis and interpretation of models. This paper focuses on the formulation aspects of modeling so that the task can be supported by decision support systems (DSS) environments. Given the knowledge intensive nature of the formulation process, the development of a modeling tool requires explicating the knowledge pertaining to modeling. This involves comprehending not only the static knowledge about model components (e.g. decision variables, coefficients, associated indices and constants), but also the process knowledge required to construct models from model pieces. The proposed top-down approach configures equations by exploiting the structural modeling knowledge inherent in equation components. The possible representation of equations at various abstraction levels is introduced, the aim being to uncover the structural model components together with the process knowledge required for their appropriate configuration. As part of developing this conceptual model, the role of semantic and syntactic information in model building is investigated. The paper proposes an approach where the formulation semantics are captured as a simple 'action-resource' view which composes models by identifying and piecing together the equation components. The process of equation construction is illustrated with examples from the linear programming (LP) modeling domain. The proposed top-down approach is contrasted with a bottom-up method.     

A data/knowledge paradigm for the modeling and design of operationssupport systems

The paper develops the Smart Object paradigm and its instantiation, which provide a new conceptualization for the modeling, design, and development of an important but little researched class of information systems, operations support systems (OSS). OSS is the authors' term for systems which provide interactive support for the management of large, complex operations environments, such as manufacturing plants, military operations, and large power generation facilities. The most salient feature of an OSS is its dynamic nature. The number and kind of elements composing the system as well as the mode of control of those elements change frequently in response to the environment. The abstraction of control and the ease with which complex dynamic control behavior can be modeled and simulated is one of the important aspects of the paradigm. The framework for the Smart Object paradigm is the fusion of object-oriented design models with declarative knowledge representation and active inferencing from AI models. Additional defining concepts from data/knowledge models, semantic data models, active databases, and frame based systems, are added to the synthesis as justified by their contribution to the ability to naturally model OSS at a high level of abstraction. The model assists in declaratively representing domain data/knowledge and its structure, and task or process knowledge, in addition to modeling multilevel control and interobject coordination     

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.     

Methoden zum Management von Informationsquellen für die Unterstützung von Softwareproduktmanagern in der Energiewirtschaft

The German energy market is facing several challenges due to changes in regulation, technical advancements as well as increasing energy costs and climate achievements like CO₂ reduction. This results in changing requirements for companies in the energy market and thus business information systems, which support their core tasks and processes. Software product managers in energy and software developing companies in charge of driving the functional development of information systems have to deal with these challenges and need to develop new information systems or enhance existing ones. Conceptual models proved helpful to design and implement information systems within several industries. However, identification and management of models as well as impact analysis of model changes results difficult. This contribution describes methods to construct, use and maintain a domain specific reference model catalog to support requirements analysis for software product manager in the German electricity and gas market.     

Learner modeling for adaptive scaffolding in a Computational Thinking-based science learning environment

Learner modeling has been used in computer-based learning environments to model learners’ domain knowledge, cognitive skills, and interests, and customize their experiences in the environment based on this information. In this paper, we develop a learner modeling and adaptive scaffolding framework for Computational Thinking using Simulation and Modeling (CTSiM)—an open ended learning environment that supports synergistic learning of science and Computational Thinking (CT) for middle school students. In CTSiM, students have the freedom to choose and coordinate use of the different tools provided in the environment, as they build and test their models. However, the open-ended nature of the environment makes it hard to interpret the intent of students’ actions, and to provide useful feedback and hints that improves student understanding and helps them achieve their learning goals. To address this challenge, we define an extended learner modeling scheme that uses (1) a hierarchical task model for the CTSiM environment, (2) a set of strategies that support effective learning and model building, and (3) effectiveness and coherence measures that help us evaluate student’s proficiency in the different tasks and strategies. We use this scheme to dynamically scaffold learners when they are deficient in performing their tasks, or they demonstrate suboptimal use of strategies. We demonstrate the effectiveness of our approach in a classroom study where one group of 6th grade students received scaffolding and the other did not. We found that students who received scaffolding built more accurate models, used modeling strategies effectively, adopted more useful modeling behaviors, showed a better understanding of important science and CT concepts, and transferred their modeling skills better to new scenarios.     

信息抽取中领域本体建模方法研究

近几年来,本体作为一种知识重用、知识共享和建模的重要工具,尤其是领域本体,在信息抽取系统中扮演着越来越重要的角色。但是,目前领域本体的创建还缺乏系统的、工程化的方法。首先介绍了本体的概念及本体的建模准则,然后分析了现有的几种常见的本体建模方法,并通过对比分析各种方法的优缺点,再结合信息抽取的原理以及软件工程的思想,提出了一种新的领域本体的建模方法。该方法具有很强的逻辑性和可操作性,可被一些领域本体在建立时采用。     

Knowledge Acquisition Advisor (KA): An interactive knowledge-acquisition tool for expert system development

A new interactive knowledge acquisition tool, called Knowledge Acquisition Advisor (KA²), is presented in this paper. The new tool will help knowledge engineers to conduct effective knowledge-elicitation interviews with domain experts through structured knowledge acquisition for both analytic and synthetic problems. A graphic modeling data structure, called Knowledge Graph is proposed, which allows knowledge engineers to model domain problems with their images and understanding. By using Knowledge Graph, knowledge engineers are able to decompose a domain problem into several components, to model the feature of each component, and to explore their relations by linking them with sets of questions. These questions can later be employed to guide the KA interview. Moreover, KA² is particularly useful for interview through computer networks, so the knowledge acquisition can take place remotely.     

元建模技术研究进展

随着UML(unified modeling language)与MDA(model driven architecture)的兴起和流行,模型已经成为软件开发的核心制品,而模型重要性的提升使得建模语言以及定义建模语言的元模型逐渐成为软件开发中的一个核心要素.软件开发往往涉及多个领域,而不同的领域往往需要不同的建模语言及其建模工具.但是,手工地为不同的建模语言开发建模工具代价高昂.元建模技术是解决这个问题的方法之一,通过元建模,可以根据领域需要定制合适的元模型以定义领域建模语言,进而自动生成支持该建模语言的建模工具.大量的工程实践表明,与领域建模以及MDA相结合,元建模可以大幅度地提高软件开发效率,基于元建模的MDA比基于通用建模语言的MDA更具潜力.在最近的几年中,元建模及其相关技术发展迅猛,不但在技术上取得了长足的进步,而且在产业界也开始出现大规模的商业应用.总结了元建模的现有研究成果,分析和比较了现有元建模工具,探讨了元建模的可能发展方向.对元建模中存在的问题进行分析,并指出了可能的解决途径.