基于Petri网的流程变体合并方法

业务融合时往往需要将已有的多个流程合并,从而形成新的满足实际需求的业务流程,如何识别已有业务流的共性特征来消除流程冗余具有较大的实际应用价值。因此,提出了一种基于Petri网的流程变体合并方法。首先,由计算匹配分数算法计算多个流程变体间不同组合的匹配分数,由此来选定一对匹配分数最高的流程变体组合;然后,根据提出的合并算法提取流程变体组合的公共部分,创建对应的副本,并将流程变体间存在的差异使用可配置连接符的分支进行合并,进而生成单个可配置的流程模型。合并后的流程模型可以捕获输入模型的所有行为,且可以对模型中的节点溯源,以此来判定节点来自于哪个流程变体。     

Protos2CPN: using colored Petri nets for configuring and testing business processes

Protos is a popular tool for business process modelling used in more than 1,500 organizations. It has a built-in Petri-net-based simulation engine which shows key performance indicators for the modelled processes. Reference process models offered for Protos reduce modelling efforts by providing generic solutions which only need to be adapted to individual requirements. However, the user can neither inspect or interact with simulations running in Protos, nor does Protos provide any explicit support for the adaptation of reference models. Hence, we aim at a more open and configurable simulation solution. To realize this we provide two transformations from Protos models to colored Petri nets (CPNs), which can be executed by CPN Tools. The first transformation enables the usage of the extensive simulation and measuring features of CPN Tools for the simulation of Protos models. The second transformation creates colored Petri nets with dedicated features for process configuration. Such configurable process models can be restricted directly within the process model without changing the model’s structure and provide therefore dedicated adaptation features for Protos’ reference process models.     

A Model to Create Organizational Value with Big Data Analytics

Value creation is a major factor not only in the sustainability of organizations but also in the maximization of profit, customer retention, business goals fulfillment, and revenue. When the value is intended to be created from Big Data scenarios, value creation entails being understood over a broader range of complexity. A question that arises here is how organizations can use this massive quantity of data and create business value? The present study seeks to provide a model for creating organizational value using Big Data Analytics (BDA). To this end, after reviewing the related literature and interviewing experts, the BDA-based organizational value creation model is developed. Accordingly, five hypotheses are formulated, and a questionnaire is prepared. Then, the respective questionnaire is given to the research statistical population (i.e., IT managers and experts, particularly those specializing in data analysis) to test the research hypotheses. In next phase, connections between model variables are scrutinized using the structural equation modeling (measurement and structural models). The results of the study indicate that investigating the infrastructures of the Big Data Analytics, as well as the capabilities of the organization and those of Big Data Analytics is the initial requirement to create organizational value using BDA. Thereby, the Big Data Analytics strategy is formulated, and ultimately, the organizational value is created as well.     

Modeling functional requirements for configurable content- and context-aware dynamic service selection in business process models

In this article, we propose a meta-model for formal specification of functional requirements for configurable content- and context-aware dynamic service selection in business process models with the objective to enable greater flexibility of the modeled processes. The dynamic service selection can cope with highly dynamic business environments that today's business processes must handle. Modeling functional requirements for dynamic service selection in business process models is not well covered in literature. Some partial solutions exist but none of them allows modeling a complete set of functional requirements for the selection similar to the one we are addressing in this article. Our meta-model enables formal specification of service selection relevant data extracted from service request message, custom configuration data (e.g., thresholds), process and task definition/instance metadata, and service selection rules. The meta-model is configurable and content- and context-aware. Processes leveraging our meta-model can adapt to changing requirements without redesign of the process flow. Proposed meta-model allows users to additionally configure the models at run time (e.g., raising a threshold). Modeling can be divided into roles with different required competences. We implement our meta-model in BPMN 2.0 (Business Process Model and Notation) through specific extensions to the BPMN semantic and diagram elements. By measuring complexity of real-world sample process models we show that using our solution modelers can efficiently model business processes that need to address frequent changing demands. Compared to available alternatives, models using our solution have on average ～13% fewer activities, ～16% fewer control-flow elements and ～22% fewer control paths. By reading ～10% smaller models (by volume) model readers get more flexible process models that capture all functional requirements for the dynamic selection.     

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modeling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modeling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modeling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.     

业务过程的自动配置与管理

一个可配置的业务过程模型可以通过配置来满足组织的特定要求。配置活动需要自动确定一个可配置过程模型的变体,同时保证该特定过程模型的正确性。然而,很少有方法能够解决此问题。提出一种新方法,即先将可配置的过程模型自动分离成原子子过程模型,再由这些模型组合成需要的过程模型,该方法能保证得到的过程模型的正确性(该过程模型无异常行为问题)。与现有的方法相比,新方法与特定的语言无关,而且避免了独立处理配置活动,降低了计算复杂度。     

E-MEMO: Referenzmodelle zur ökonomischen Realisierung leistungsfähiger Infrastrukturen für Electronic Commerce

For many companies, the development of a competitive E-Commerce strategy and even more so its implementation is a huge challenge. This paper presents a method that is aimed at reducing substantially cost and risk of such an endeavour. The method has been adapted from an existing method for multi-perspective enterprise modelling. It supports strategy analysis and design as well as the corresponding organisational design. It also fosters the configuration of supporting information systems. Besides specialized process models, the method offers reference models for strategy design and a library of business process models. The process models can be transformed automatically into workflow schemata.     

Referenzmodellierung im Data-Warehousing — State-of-the-Art und konfigurative Ansätze für die Fachkonzeption

Reference models increase the efficiency of data warehouse projects by providing construction patterns. This paper presents an overview of existing applications of reference models for data warehousing which shows that there is only insufficient support of model alternatives during requirements definition. Especially configurable reference models provide an adequate solution for creating project-specific models. Therefore, we suggest an extension of data warehouse modeling techniques by configuration rules. The configuration of reference models is embedded in the data warehouse development process. Furthermore, supplementary operational instructions for reference model designers are outlined.     

SaaS流程可配置模型的研究与实现

目前针对软件即服务SaaS(Software as a Service)的可配置策略还没有完全形成成熟的理论。借鉴已有技术,提出和描述基于组件组装定制服务的一种配置模型。该配置模型允许用户对服务进行建模,根据自己特定的业务流程,基于相同的服务组件,通过定义不同的数据关联和约束规则实现服务流程定制。最后通过两个业务需求不同的服务的配置实例,证明所描述方法的灵活性和可行性。     

Selecting highly optimal architectural feature sets with Filtered Cartesian Flattening

Feature modeling is a common method used to capture the variability in a configurable application. A key challenge developers face when using a feature model is determining how to select a set of features for a variant that simultaneously satisfy a series of resource constraints. This paper presents an approximation technique for selecting highly optimal feature sets while adhering to resource limits. The paper provides the following contributions to configuring application variants from feature models: (1) we provide a polynomial time approximation algorithm for selecting a highly optimal set of features that adheres to a set of resource constraints, (2) we show how this algorithm can incorporate complex configuration constraints; and (3) we present empirical results showing that the approximation algorithm can be used to derive feature sets that are more than 90%+ optimal.     

Ensuring correctness during process configuration via partner synthesis

Variants of the same process can be encountered within one organization or across different organizations. For example, different municipalities, courts, and rental agencies all need to support highly similar processes. In fact, procurement and sales processes can be found in almost any organization. However, despite these similarities, there is also the need to allow for local variations in a controlled manner. Therefore, many academics and practitioners have advocated the use of configurable process models (sometimes referred to as reference models). A configurable process model describes a family of similar process models in a given domain. Such a model can be configured to obtain a specific process model that is subsequently used to handle individual cases, for instance, to process customer orders. Process configuration is notoriously difficult as there may be all kinds of interdependencies between configuration decisions. In fact, an incorrect configuration may lead to behavioral issues such as deadlocks and livelocks. To address this problem, we present a novel verification approach inspired by the “operating guidelines” used for partner synthesis. We view the configuration process as an external service, and compute a characterization of all such services which meet particular requirements via the notion of configuration guideline. As a result, we can characterize all feasible configurations (i.e., configurations without behavioral problems) at design time, instead of repeatedly checking each individual configuration while configuring a process model.     

面向产品线交互配置不一致性修复的差分IBEA算法

在大规模复杂系统产品线工程中,人工配置难免会导致配置的不一致,即,配置数据会违背预定义的约束(也可以称为一致性约束).对于大规模复杂系统产品线体系结构,比如信息物理系统产品线,往往存在成百上千的可变点以及约束,而且约束与可变点之间存在复杂的依赖关系,为不一致配置的修复带来很大的挑战.为了解决这个问题,针对前期提出的基于多目标搜索以及约束求解技术的自动不一致配置修复推荐框架(Zen-Fix),提出一种改进的IBEA算法(De IBEA).De IBEA通过将差分引入IBEA算法,搜索过程中,基于可行解和不可行解的差分变异产生后代,最终为用户推荐符合预定义约束并且对于配置效率来说最优的配置修复方案.基于一个工业案例海底油田采控系统产品线为例,通过模拟一个产品的配置过程,产生了10 189个优化问题,结果表明:Zen-Fix框架结合De IBEA算法,可以实时地为用户提供较优的不一致配置修复方案.此外,通过对这10 189个问题的推荐方案进行对比,证明了De IBEA算法无论从时间效率还是搜索性能上都优于原始的IBEA算法.     

Generating optimized configurable business process models in scenarios subject to uncertainty

ContextThe quality of business process models (i.e., software artifacts that capture the relations between the organizational units of a business) is essential for enhancing the management of business processes. However, such modeling is typically carried out manually. This is already challenging and time consuming when (1) input uncertainty exists, (2) activities are related, and (3) resource allocation has to be considered. When including optimization requirements regarding flexibility and robustness it becomes even more complicated potentially resulting into non-optimized models, errors, and lack of flexibility.ObjectiveTo facilitate the human work and to improve the resulting models in scenarios subject to uncertainty, we propose a software-supported approach for automatically creating configurable business process models from declarative specifications considering all the aforementioned requirements.MethodFirst, the scenario is modeled through a declarative language which allows the analysts to specify its variability and uncertainty. Thereafter, a set of optimized enactment plans (each one representing a potential execution alternative) are generated from such a model considering the input uncertainty. Finally, to deal with this uncertainty during run-time, a flexible configurable business process model is created from these plans.ResultsTo validate the proposed approach, we conduct a case study based on a real business which is subject to uncertainty. Results indicate that our approach improves the actual performance of the business and that the generated models support most of the uncertainty inherent to the business.ConclusionsThe proposed approach automatically selects the best part of the variability of a declarative specification. Unlike existing approaches, our approach considers input uncertainty, the optimization of multiple objective functions, as well as the resource and the control-flow perspectives. However, our approach also presents a few limitations: (1) it is focused on the control-flow and the data perspective is only partially addressed and (2) model attributes need to be estimated.     

A new integrated on-line fuzzy clustering and segmentation methodology with adaptive PCA approach for process monitoring and fault detection and diagnosis

A new on-line fuzzy clustering-based algorithm is developed using integration of an adaptive principal component analysis approach with a weighted fuzzy C-means (WFCM) methodology for process fault detection and diagnosis (FDD) applications. The proposed algorithm is based on the segmentation of measured multivariate time series process data through a sliding window scheme being realized in a bottom-up cluster merging approach to enable detection of probable changes embedded in their hidden structure. The method recursively maintain updated PCA models and their corresponding fuzzy membership functions based on the most recent arrival of each independent chunk of process data. The extracted chunk features are then retained in the memory to be merged using a new on-line fuzzy C-means methodology before incoming of the following chunks of data. A new formula is then presented for cluster merging improvement by incorporating an on-line weight to address the issue of cluster’s weight updating in the on-line WFCM methodology. The cluster merging mechanism is coordinated by a compatibility criterion, utilizing both similarities of the adapted clusters-based PCA models and their center closeness. The proposed algorithm has been evaluated on an artificial case study and Tennessee Eastman benchmark process plant. The observed performances demonstrate promising capabilities of the proposed algorithm to successfully detect and diagnose the introduced fault scenarios.     

基于Petri网行为紧密度的业务流程配置优化分析

业务流程优化分析是业务流程管理的重要内容之一,存在配置信息的优化分析显得尤为重要。已有研究主要集中于业务流程优化分析,但对于存在配置信息的业务流程优化则存在不足。对业务流程配置优化分析进行了研究,提出了日志与业务流程Petri网模型的紧密度计算方法 以及基于行为紧密度的业务流程配置优化分析方法。首先根据给定事件日志的执行序列及实例数建立初始模型,计算初始模型与剩余日志的紧密度,利用紧密度大的日志优化初始模型;然后引进配置变迁对初步优化后的模型进行进一步优化;最后通过一个简单的实例说明了该方法的可行性。     

On the testing of user‐configurable software systems using firewalls

User‐configurable software systems present many challenges to software testers. These systems are created to address a large number of possible uses, each of which is based on a specific configuration. As configurations are made up of groups of configurable elements and settings, a huge number of possible combinations exist. As it is infeasible to test all configurations before release, many latent defects remain in the software once deployed. A just‐in‐time testing technique is presented to address this problem, including examples of how it can be used with various user‐configurable systems in the field. The proposed solution is evaluated with a set of five empirical studies conducted on two separate ABB software systems using real customer configurations and changes. These studies analyse failures reported by many different customers globally and show that this just‐in‐time testing process is effective at detecting latent defects exposed by customer configuration changes in user‐configurable systems. Copyright © 2010 John Wiley & Sons, Ltd.