Model-based incremental conformance checking to enable interactive product configuration

ContextModel-based product line engineering (PLE) is a paradigm that can enable automated product configuration of large-scale software systems, in which models are used as an abstract specification of commonalities and variabilities of products of a product line.ObjectiveIn the context of PLE, providing immediate feedback on the correctness of a manual configuration step to users has a practical impact on whether a configuration process with tool support can be successfully adopted in practice.MethodIn an existing work, a UML-based variability modeling methodology named as SimPL and an interactive configuration process was proposed. Based on the existing work, we propose an automated, incremental and efficient conformance checking approach to ensure that the manual configuration of a variation point conforms to a set of pre-defined conformance rules specified in the Object Constraint Language (OCL). The proposed approach, named as Zen-CC, has been implemented as an integrated part of our product configuration and derivation tool: Zen-Configurator.ResultsThe performance and scalability of Zen-CC have been evaluated with a real-world case study. Results show that Zen-CC significantly outperformed two baseline engines in terms of performance. Besides, the performance of Zen-CC remains stable during the configuration of all the 10 products of the product line and its efficiency also remains un-impacted even with the growing product complexity, which is not the case for both of the baseline engines.ConclusionThe results suggest that Zen-CC performs practically well and is much more scalable than the two baseline engines and is scalable for configuring products with a larger number of variation points.     

基于UML的软件体系结构建模方法研究

模型的有效集成是软件系统建模的关键。然而,通常基于UML的软件系统的四个模型中,从用例分析模型到其它设计模型之间存在一条很难逾越的鸿沟。本文通过引入软件体系结构模型,提出了基于UML的软件体系结构建模方法,进一步完善了软件系统的建模。     

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.     

Improving software product line configuration: A quality attribute-driven approach

ContextDuring the definition of software product lines (SPLs) it is necessary to choose the components that appropriately fulfil a product’s intended functionalities, including its quality requirements (i.e., security, performance, scalability). The selection of the appropriate set of assets from many possible combinations is usually done manually, turning this process into a complex, time-consuming, and error-prone task.ObjectiveOur main objective is to determine whether, with the use of modeling tools, we can simplify and automate the definition process of a SPL, improving the selection process of reusable assets.MethodWe developed a model-driven strategy based on the identification of critical points (sensitivity points) inside the SPL architecture. This strategy automatically selects the components that appropriately match the product’s functional and quality requirements. We validated our approach experimenting with different real configuration and derivation scenarios in a mobile healthcare SPL where we have worked during the last three years.ResultsThrough our SPL experiment, we established that our approach improved in nearly 98% the selection of reusable assets when compared with the unassisted analysis selection. However, using our approach there is an increment in the time required for the configuration corresponding to the learning curve of the proposed tools.ConclusionWe can conclude that our domain-specific modeling approach significantly improves the software architect’s decision making when selecting the most suitable combinations of reusable components in the context of a SPL.     

A pattern-based model-driven approach for situational method engineering

ContextConstructing bespoke software development methodologies for specific project situations has become a crucial need, giving rise to Situational Method Engineering (SME). Compared with Software Engineering, SME has a long way to go yet; SME approaches are especially deficient as to support for modeling, portability, and automation. Model-Driven Development (MDD) has been effectively used for addressing these issues in Software Engineering, and is also considered a promising approach for resolving them in SME.ObjectiveThis paper aims to address the shortcomings of existing SME approaches by introducing a novel MDD approach, specifically intended for SME purposes, that uses a pattern-based approach for model transformation.MethodDeveloping a MDD approach for SME requires that a modeling framework, consisting of modeling levels, be defined for modeling software development methodologies. Transformation patterns should also be specified for converting the models from one level to the next. A process should then be defined for applying the framework and transformations patterns to real SME projects. The resulting MDD approach requires proper evaluation to demonstrate its applicability.ResultsA framework and a semi-automated process have been proposed that adapt pattern-based model transformation techniques for application to the methodology models used in SME. The transformation patterns have been implemented in the Medini-QVT model transformation tool, along with two supplementary method bases: one for mapping the situational factors of SME projects to requirements, and the other for mapping the requirements to method fragments. The method engineer can produce the methodology models by using the method bases and executing the transformation patterns via the tool.ConclusionThe validity of the proposed approach has been assessed based on special evaluation criteria, and also through application to a real-world project. Evaluation results indicate that the proposed approach addresses the deficiencies of existing approaches, and satisfies the practicality requirements of SME approaches.     

Synergy between Activity Theory and goal/scenario modeling for requirements elicitation,analysis, and evolution

ContextIt is challenging to develop comprehensive, consistent, analyzable requirements models for evolving requirements. This is particularly critical for certain highly interactive types of socio-technical systems that involve a wide range of stakeholders with disparate backgrounds; system success is often dependent on how well local social constraints are addressed in system design.ObjectiveThis paper describes feasibility research, combining a holistic social system perspective provided by Activity Theory (AT), a psychological paradigm, with existing system development methodologies and tools, specifically goal and scenario modeling.MethodAT is used to understand the relationships between a system, its stakeholders, and the system’s evolving context. The User Requirements Notation (URN) is used to produce rigorous, analyzable specifications combining goal and scenario models. First, an AT language was developed constraining the framework for automation, second consistency heuristics were developed for constructing and analyzing combined AT/URN models, third a combined AT/URN methodology was developed, and consequently applied to a proof-of-concept system.ResultsAn AT language with limited tool support was developed, as was a combined AT/URN methodology. This methodology was applied to an evolving disease management system to demonstrate the feasibility of adapting AT for use in system development with existing methodologies and tools. Bi-directional transformations between the languages allow proposed changes in system design to be propagated to AT models for use in stakeholder discussions regarding system evolution.ConclusionsThe AT framework can be constrained for use in requirements elicitation and combined with URN tools to provide system designs that include social system perspectives. The developed AT/URN methodology can help engineers to track the impact on system design due to requirement changes triggered by changes in the system’s social context. The methodology also allows engineers to assess the impact of proposed system design changes on the social elements of the system context.     

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

ContextIn industrial settings products are developed by more than one organization. Software vendors and suppliers commonly typically maintain their own product lines, which contribute to a larger (multi) product line or software ecosystem. It is unrealistic to assume that the participating organizations will agree on using a specific variability modeling technique—they will rather use different approaches and tools to manage the variability of their systems.ObjectiveWe aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations.MethodWe present an integrative approach that provides a unified perspective to users configuring products in multi product line environments, regardless of the different modeling methods and tools used internally. We also present a technical infrastructure and a prototype implementation based on web services.ResultsWe show the feasibility of the approach and its implementation by using it with the three most widespread types of variability modeling approaches in the product line community, i.e., feature-based, OVM-style, and decision-oriented modeling. To demonstrate the feasibility and flexibility of our approach, we present an example derived from industrial experience in enterprise resource planning. We further applied the approach to support the configuration of privacy settings in the Android ecosystem based on multiple variability models. We also evaluated the performance of different model enactment strategies used in our approach.ConclusionsTools and techniques allowing stakeholders to handle variability in a uniform manner can considerably foster the initiation and growth of software ecosystems from the perspective of software reuse and configuration.     

基于多色集合的大规模产品定制形式化解决方法

为了满足大规模定制中客户的个性化要求, 以产品族设计为研究对象, 提出了基于多色集合层次理论的产品族配置建模方法。利用元素、个人颜色、统一颜色等概念, 建立产品族模型与客户需求之间的映射关系, 提供产品族元素选择的形式解决方案, 实现用户需求到不同产品组合方案的推理过程。实例验证结果表明, 该建模方法简便易行, 便于形式化表述和软件实现。     

A model-driven approach for the derivation of architectural requirements of software product lines

The alignment of the software architecture and the functional requirements of a system is a demanding task because of the difficulty in tracing design elements to requirements. The four-step rule set (4SRS) is a unified modeling language (UML)-based model-driven method for single system development which provides support to the software architect in this task. This paper presents an evolution of the 4SRS method aimed at software product lines. In particular, we describe how to address the transformation of functional requirements (use cases) into component-based requirements for the product line architecture. The result is a UML-based model-driven method that can be applied in combination with metamodeling tools such as the eclipse modeling framework (EMF) to derive the architecture of software product lines. We present our approach in a practical way and illustrate it with an example. We also discuss how our proposals are related to the work of other authors.     

The DOPLER meta-tool for decision-oriented variability modeling: a multiple case study

The variability of a product line is typically defined in models. However, many existing variability modeling approaches are rigid and don’t allow sufficient domain-specific adaptations. We have thus been developing a flexible and extensible approach for defining product line variability models. Its main purposes are to guide stakeholders through product derivation and to automatically generate product configurations. Our approach is supported by the DOPLER (Decision-Oriented Product Line Engineering for effective Reuse) meta-tool that allows modelers to specify the types of reusable assets, their attributes, and dependencies for their specific system and context. The aim of this paper is to investigate the suitability of our approach for different domains. More specifically, we explored two research questions regarding the implementation of variability and the utility of DOPLER for variability modeling in different domains. We conducted a multiple case study consisting of four cases in the domains of industrial automation systems and business software. In each of these case studies we analyzed variability implementation techniques. Experts from our industry partners then developed domain-specific meta-models, tool extensions, and variability models for their product lines using DOPLER. The four cases demonstrate the flexibility of the DOPLER approach and the extensibility and adaptability of the supporting meta tool.     

基于UML的集成化CASE平台的研究和实现

统一建模语言提供了研制和开发面向对象软件集成化开发环境的理论基础,指出UML本质上是一套文档符号,提出UML增减原则:是否有利于自动文档生成;是否有利于自动程序生成。提出一个“开环”的集成化开发平台的构造框架。最后,基于上述设计思想和结合软件项目实际情况,开发出一个集成化CASE平台,平台具有数据库文档自动生成、界面自动生成、代码自动生成和构件重用等功能。     

Platform-based product design and development: A knowledge-intensive support approach

This paper presents a knowledge-intensive support paradigm for platform-based product family design and development. The fundamental issues underlying the product family design and development, including product platform and product family modeling, product family generation and evolution, and product family evaluation for customization, are discussed. A module-based integrated design scheme is proposed with knowledge support for product family architecture modeling, product platform establishment, product family generation, and product variant assessment. A systematic methodology and the relevant technologies are investigated and developed for knowledge supported product family design process. The developed information and knowledge-modeling framework and prototype system can be used for platform product design knowledge capture, representation and management and offer on-line support for designers in the design process. The issues and requirements related to developing a knowledge-intensive support system for modular platform-based product family design are also addressed.     

Simulating evolution in model-based product line engineering

ContextNumerous approaches are available for modeling product lines and their variability. However, the long-term impacts of model-based development on maintenance effort and model complexity can hardly be investigated due to a lack of empirical data. Conducting empirical research in product line engineering is difficult as companies are typically reluctant to provide access to data from their product lines. Also, many benefits of product lines can be measured only in longitudinal studies, which are difficult to perform in most environments.ObjectiveIn this paper, we thus aim to explore the benefit of simulation to investigate the evolution of model-based product lines.MethodWe present a simulation approach for exploring the effects of product line evolution on model complexity and maintenance effort. Our simulation considers characteristics of product lines (e.g., size, dependencies in models) and we experiment with different evolution profiles (e.g., technical refactoring vs. placement of new products).ResultsWe apply the approach in a simulation experiment that uses data from real-world product lines from the domain of industrial automation systems to demonstrate its feasibility.ConclusionOur results demonstrate that simulation contributes to understanding the effects of maintenance and evolution in model-based product lines.     

Product platform design through sensitivity analysis and cluster analysis

Scale-based product platform design consists of platform configuration to decide which variables are shared among which product variants, and selection of the optimal values for platform (shared) and non-platform variables for all product variants. The configuration step plays a vital role in determining two important aspects of a product family: efficiency (cost savings due to commonality) and effectiveness (capability to satisfy performance requirements). Many existing product platform design methods ignore it, assuming a given platform configuration. Most approaches, whether or not they consider the configuration step, are single-platform methods, in which design variables are either shared across all product variants or not shared at all. In multiple-platform design, design variables may be shared among variants in any possible combination of subsets, offering opportunities for superior overall design but presenting a more difficult computational problem. In this work, sensitivity analysis and cluster analysis are used to improve both efficiency and effectiveness of a scale-based product family through multiple-platform product family design. Sensitivity analysis is performed on each design variable to help select candidate platform design variables and to provide guidance for cluster analysis. Cluster analysis, using performance loss due to commonization as the clustering criterion, is employed to determine platform configuration. An illustrative example is used to demonstrate the merits of the proposed method, and the results are compared with existing results from the literature.     

Systematizing requirements elicitation technique selection

ContextThis research deals with requirements elicitation technique selection for software product requirements and the overselection of open interviews.ObjectivesThis paper proposes and validates a framework to help requirements engineers select the most adequate elicitation techniques at any time.MethodWe have explored both the existing underlying theory and the results of empirical research to build the framework. Based on this, we have deduced and put together justified proposals about the framework components. We have also had to add information not found in theoretical or empirical sources. In these cases, we drew on our own experience and expertise.ResultsA new validated approach for requirements technique selection. This new approach selects techniques other than open interview, offers a wider range of possible techniques and captures more requirements information.ConclusionsThe framework is easily extensible and changeable. Whenever any theoretical or empirical evidence for an attribute, technique or adequacy value is unearthed, the information can be easily added to the framework.     

A Semantic Web-Based Approach to Knowledge Management for Grid Applications

Knowledge has become increasingly important to support intelligent process automation and collaborative problem solving in large-scale science over the Internet. This paper addresses distributed knowledge management, its approach and methodology, in the context of grid application. We start by analyzing the nature of grid computing and its requirements for knowledge support; then, we discuss knowledge characteristics and the challenges for knowledge management on the grid. A semantic Web-based approach is proposed to tackle the six challenges of the knowledge lifecycle - namely, those of acquiring, modeling, retrieving, reusing, publishing, and maintaining knowledge. To facilitate the application of the approach, a systematic methodology is conceived and designed to provide a general implementation guideline. We use a real-world Grid application, the GEODISE project, as a case study in which the core semantic Web technologies such as ontologies, semantic enrichment, and semantic reasoning are used for knowledge engineering and management. The case study has been fully implemented and deployed through which the evaluation and validation for the approach and methodology have been performed     

Development of a computer-aided concurrent net shape product and process development environment

This paper presents a systematic approach to developing a collaborative environment for computer-aided concurrent net shape product and process development. This approach includes the steps of (1) conventional development process analysis, (2) development process re-engineering, (3) computer-based system functional requirements analysis, (4) system framework design, and (5) system modeling, integration and implementation. This environment can support concurrent net shape product and process development by providing and integrating functions of product data management, process management and development advisory tools. The results of this research will facilitate the rationalization and automation of net shape product and process development and thus improve the efficiency and quality, and reduce the cost of net shape product development.

IDEF structural analysis methodology was employed to capture the characteristics of net shape product and process development process. The concept of concurrent engineering was used to re-engineer the development process. The technology of system engineering was used to design the computer-aided system framework. Object-oriented analysis, modeling and design methodology, knowledge engineering and data engineering techniques were employed for system modeling and implementation.     

Towards a seamless integration between process modeling descriptions at business and production levels: work in progress

To fulfill increasing requirements in the manufacturing sector, companies are facing several challenges. Three major challenges have been identified regarding time-to-market, vertical feedback loops, and level of automation. Grafchart, a graphical language aimed for supervisory control applications, can be used from the process-planning phase, through the implementation phase and all the way to the phase for execution of the process control logics, on the lower levels of the automation triangle along the life cycle axis. This work in progress examines that the same process-based engineering approach can be used on the higher levels of the automation triangle along the enterprise axis interconnecting both axes. By splitting the execution engine and the visualization engine of Grafchart various different visualization tools could potentially be used, however connected by the shared Grafchart semantics. Traditional Business languages (e.g. BPMN) could therefore continue to be used for the process-planning phase whereas traditional production languages (e.g. Grafchart or other sequential function charts-like languages) could be used for the execution. Since they are connected through the semantics, advantages regarding the three identified challenges could be achieved: time-to-market could be reduced, the time delays in the vertical feedback loops could be reduced by Key Performance Indicator visualization and eventing, and the level of automation could be increased.     

Automated Compliance Checking Methodology for Non-Log Operations

ABSTRACT

Compliance Management (CM) is the management process that an organization implements to ensure organizational compliance with relevant requirements and expectations. The most complicated, time-consuming, and costly process in CM is compliance checking because it requires a person who has a good knowledge in policy to examine whether the current operations meet the policy requirements. Many researchers have tried to study better ways to automate the compliance checking process, but most of them require the operation logs in to the computer systems. This paper proposes a methodology to enable the automation of compliance checking for those operations that have no log in computer systems by using questions and answers principle to cooperate with the semantic web technologies. Since there are some operations that cannot be understood by computer systems, using questions is one way to gather the answers, such as operation log to evaluate their compliance. The proposed methodology can help noncertified auditors perform the compliance checking so that the time and cost of compliance checking would be greatly reduced.