Among different types of changes, a specific type named long-tailed change (LTC), induced by wide-spectrum and sporadic events (hereafter long-tailed business events (LBEs), poses fresh challenges to available change management solutions in business process management. The disorder in economic and social life caused by the competition of COVID-19 epidemics and countermeasures all over the world fully demonstrates the impact of this new change management problem. Based on the principle of separation of concerns, this paper proposes a systematic framework to solve the above problem. The solution consists of a low-code mechanism for process adaptation and business policy conformance. As a result, front-line practitioners can quickly react to changes by using a domain-specific language (DSL) while a corresponding verification of functional and non-functional attributes maintains compliance with business constraints. We validate the solution through a case study of an e-commerce scenario during the COVID-19 pandemic.

Due to its ease of use, the notion of Simple Temporal Networks with Uncertainty (STNU) has been successfully used in verifying temporal constraints of business processes. Considering the universality of non-functional attributes, it is significant to generalize STNU in characterizing these non-functional constraints, resulting in a better expressiveness to support process modeling and business applications. In this paper, we leverage STNU to such a level by using abstract algebra on STNU. It results in a general non-functional constraint modeling and verification method in business process management (BPM), from the original temporal constraints to broader qualitative and quantitative ones, which is not yet supported with STNU in the BPM. Based on the proposed method, we demonstrate the capability of verifying dynamic controllability (DC) for these non-functional attributes, such as satisfaction, reputation grade, etc.

By leveraging IoT Big Data, BPM can gain real-time physical world information to make faster and more accurate decisions, but there is a technical gap between IoT sensors and businesses. To bridge the gap, an event penetration mechanism from IoT sensors to business processes is proposed along a practical case study. This paper presents a concrete IoT-BPM application case dealing with seaborne safety ensurance in transporting liquefied natural gas (LNG), analyzes its technical challenges, and examines the feasibility and supposed effects of the BRIBOT approach.

To cope with the long-tailed changes, an annotation-based BPM approach has been proposed to adapts its behavior in a timely manner. It patches existing business process models rather than rebuilds models from scratch, which saves efforts and reacts to unforeseen changes quickly. However, the original annotation-based approach is at risk of improper annotations added that results in unexpected effects or leads to failure. To remedy this loophole, this paper proposes a syntax-directed annotation approach to guarantee sound reactions. we develop a scheme for designing domain specific languages based on abstract syntax trees and generating a syntax-directed editor automatically. As a result, all patched annotations on the process models are soundness guaranteed in terms of the domain specific language. Case studies demonstrate that proposed approach and tools can help domain experts to tackle long-tailed changes more easily guarantee the correct reactions.

Enterprises rely on their process-aware information system (PAIS) to conduct business. With the increasingly fierce competition, the operation environment of enterprises is constantly changing due to uncertain factors or emerging opportunities. How to react to the changes in time and make a positive response is fundamental for enterprises to maintain their core competitiveness in the new economic era. Among these changes, a kind of long-tailed change has been omitted by traditional business process management (BPM) because of its wide variety and low frequency. Just as the long-tailed effect reveals, the impact of long-tailed change on PAIS change management will be no less than the impact of high-frequency changes. On the move to digital economy, enterprises can hardly win if they cannot catch the first opportunity and deal the long-tailed changes properly. On the other hand, business process models in PAIS are core assets of an enterprise. The requirement of keeping routine processes running smoothly and reusing these assets smartly in unexpected situations runs through the whole business. To solve this problem, this paper proposes a novel maintenance approach for business process models to cope with long-tailed changes. By decorating existing process models with business-oriented annotations, the PAIS can equip with the mechanism to support original processes while react to long-tailed situations agilely with a reinforced process engine. Several experiments revels the effectiveness and generality of proposed approach for BPM in the digital economy ear.

Business process often contain many participants with different value orientations, and the fulfillment of the business value is achieved via cooperation and game among these participants in forms of services. Recently, the conceptual framework of crossover services has been constructed in pursuit of value innovation by breaking the traditional boundary and promoting convergence of service systems. Some value related factors include: 1) KPIs about activities, processes and collaborations; 2) Constraints on activities and resource utilization. The evaluation of these factors are highly dependent on participant's position, time and place of occurrence. However, in practice, such important information is not well-specified in business process models, let alone be evaluated, traced, and improved in applications. In this paper, we propose a temporal-spatial-domain ternary model to specify above information, and develop an annotation approach to attach it to standard BPMN 2.0 processes. We validate their effectiveness through case studies, and the experimental result reveals their potential advantages in pursuit of value innovation with crossover services.

Summary There are usually process model variants for a business as its application and evolution. Configurable process modeling is an effective approach for the design and development of business process models by reuse. However, the existing configurable process modeling approaches focus on traditional activity‐centric business processes, which is unfeasible for the new modeling paradigm of artifact‐centric business processes. To solve the problem, we propose a configurable modeling framework, especially for artifact‐centric business processes. To derive the integrated model for multiple process model variants, we propose a merger operation for artifact‐centric process model variants. We get a configurable artifact‐centric process model by identifying configurable points in the integrated model by common and variable characteristics. Moreover, the associated configuration alternatives are set accordingly for configurable points, in which the property of data privacy is considered. New artifact‐centric process models can be derived by configuration based on the behavior of a configurable model. To facilitate the process configuration, guidelines are analyzed based on the notion of process element relation graph. A case study is conducted to illustrate the effectiveness of our approach with a real‐world business process developed for Real Estate Administration (REA) in Hangzhou, China.

Dynamic, distributed and open business forces enterprises to support various critical requirements, such as, timely reacting to changes, properly reusing business assets and smoothly collaborating with external partners. Existing approaches focus on mechanisms dealing with heterogeneity, but there is a lack of frameworks enabling legacy business processes performing collaboration in an open service environment. This paper proposes the L2L service framework featuring reactive IoT event messaging and coordinator-based collaborating between autonomous enterprises. Along with the emerging of coordinators, L2L empowers on-the-fly business process collaboration with dynamic changes. We present our experiments with a real-world scenario from the shipping industry of China.

In this paper, we present the exact online updating formulae for the generalized inverse of centered matrices. The computational cost is O(mn) for matrices of size m × n. Experimental results validate the proposed method’s accuracy and efficiency.

Survivability is crucial for computer systems that support critical infrastructures of our society. For those in paradigm of SOA where the computing settings are intrinsically open, traditional survivability model and safeguard mechanisms are no longer applicable. To rise to the challenge, we propose a formal definition and a corresponding framework to evaluate the survivability of SOA systems. We treat survivability as a multidimensional QoS property, and then give a holistic evaluation method based on the Hidden Markov Model.

In a service-oriented system, service substitution can be used to repair faults, improve performance, and/or enhance resilience via graceful degradation. Correct service substitution must preserve the essential properties of the system, particularly the proper termination and/or liveness. However, ensuring correct service substitution poses some challenges. The main obstacle is that, in the general case, the behavior of services is opaque to service designers due to the autonomy of services. While the bulk of prior researches on service substitution assume that services advertise their interaction protocols (e.g., in the form of BPEL), existing services (i.e., in the form of WSDL) rarely do so. In this paper, we study the problem of service substitution under the assumption that services do not expose their interaction protocols. To this end, we characterize the behavior of interacting services by means of contracts consisting purely of input/output messages and message exchange patterns revealed in WSDL interfaces. On the other hand, the behavior of service compositions is assumed to be known to service designers. In this setting, we define notions of compatibility for self-contained systems and for open systems. Based on these notions, we propose a theory of contracts for service substitution. We also study a notion of degraded substitution based on the "may-", "should-" and "must-" testing pre-orders.

The ability to substitute a service for another is one of the features of Service-Oriented Computing (SOC). In this paper, we study the problem of degraded service substitution assuming that services have explicitly-defined interaction protocols, e.g., in the form of WS-BPEL business protocols. To this end, we characterize the behavior of interacting services by means of contracts specifying the allowed sequence of message sending and receiving operations. The contribution of this paper is a theory of contracts for service substitution which improve system survivability by gracefully degraded substitution.

Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noise-free data while some of them are better than others on noisy data. But in reality, ensemble methods that can consistently gain good performance in situations with or without noise are more desirable. In this paper, we propose a new method namely MTForest, to ensemble decision tree learning algorihms by enumerating each input attribute as extra task to introduce different additional inductive bias to generate diverse yet accurate component decision tree learning algorithms in the ensemble. The experimental results show that in situations without classification noise, MTForest is comparable to Boosting and Random Forest and significantly better than Bagging, while in situations with classification noise, MTForest is significantly better than Boosting and Random Forest and is slightly better than Bagging. So MTForest is a good choice for ensemble decision tree learning algorithms in situations with or without noise. We conduct the experiments on the basis of 36 widely used UCI data sets that cover a wide range of domains and data characteristics and run all the algorithms within the Weka platform.

Currently technologies of Web services have greatly developed and provided a new application platform for CSCW. For a business process across enterprises, cooperation of multiple Web services is usually required to achieve the final goal. However, most current Web services choreography proposals, such as BPEL4WS or WSCI, only provide a fixed execution flow, lacking of flexibility and adaptability. In this paper, we propose a flexible workflow model TDWF, which can specify the execution process of Web services according to task dependency information, so that the Web services can be composed dynamically. We also put forward an algorithm to verify the correctness of the composition process. Besides, the proposed compensation mechanism of workflow could properly satisfy the requirements of end users

The compatibility analysis is absolutely necessary for guaranteeing the correct composition of Web services, no matter what styles the composition takes, statically or dynamically. In this paper, we provide a formalization of Web services behavior using the approach of automata. With this understanding, we propose a definition of role among Web services interactions. As a result, we can check whether two or more Web services are compatible in collaboration or not.