Model-Driven Engineering of Process-Aware Information Systems

General-purpose modeling languages are inadequate to model and visualize business processes precisely. An enterprise has its own vocabulary for modeling processes and its specific tasks may have attached data that define the tasks precisely. We propose using Domain Specific Modeling (DSM) languages to model business processes, such that an enterprise can define its own DSM language(s) capturing its vocabulary and data requirement. We suggest using UML profiles and UML activity diagrams as the semantic base for these DSM languages and present tools that are able to create a DSM language and tool support for a given domain. One tool, called ADSpecializer, can generate a UML profile and its tool support of a given application domain. The other tool, ADModeler, is used to create UML activity diagrams within such a domain-specific UML profile. The two tools enable an enterprise to efficiently define and utilize their own DSM language.

The increasing adoption of Process-aware Information Systems (PAISs), together with the variability of Business Processes (BPs) across different application contexts, has resulted in large process model repositories with collections of related process model variants. To reduce both costs and occurrence of errors, the explicit management of variability throughout the BP lifecycle becomes crucial. In literature, several proposals dealing with BP variability have been proposed. However, the lack of a method for their systematic comparison makes it difficult to select the most appropriate one meeting current needs best. To close this gap, this work presents an evaluation framework that allows analyzing and comparing the variability support provided by existing proposals developed in the context of BP variability. The framework encompasses a set of language requirements as well as a set of variability support features. While language requirements allow assessing the expressiveness required to explicitly represent variability of different process perspectives, variability support features reflect the tool support required to properly cover such expressiveness. Our evaluation framework has been derived based on an in-depth analysis of several large real-world process scenarios, an extensive literature review, and an analysis of existing PAISs. In this vein, the framework helps to understand BP variability along the BP lifecycle. In addition, it supports PAISs engineers in deciding, which of the existing BP variability proposals meets best their needs.

Organizations that manage their Business Processes (BPs) poorly -or that not manage them at all- have well-known problems regarding their operation, both at the BPs and the Information Systems (IS) levels. Some of these problems are due to a vertical and functional vision of the organization, without any global BP vision. In this context, similar decentralized organizational units very often perform the same BPs sometimes in different ways. Moreover, some BPs are implicit in the IS supporting them. In this article we present an experience report of a BPM pilot project we have carried out within our university, as an initiative to improve BPs management and corresponding IS support. We started specifying a process map for management support BPs, and then we selected key BPs which where specified, modeled and implemented using BPMN 2.0 and Bonita BPMS, to shift the organization focus from traditional IS to Process Aware IS (PAIS).

The increasing adoption of process-aware information systems (PAISs) has resulted in a large number of implemented business processes. To react on changing needs, companies should be able to quickly adapt these process implementations if required. Current PAISs, however, only provide mechanisms to evolve the schema of a process model, but do not allow for the automated creation and adaptation of their user interfaces (UIs). The latter may have a complex logic and comprise, for example, conditional elements or database queries. Creating and evolving the UI components of a PAIS manually is a tedious and error-prone task. This technical report introduces a set of patterns for transforming fragments of a business process model, whose activities are performed by the same user role, to UI components of the PAIS. In particular, UI logic can be expressed using the same notation as for process modeling. Furthermore, a transformation method is introduced, which applies these patterns to automatically derive UI components from a process model by establishing a bidirectional mapping between process model and UI. This mapping allows propagating UI changes to the process model and vice versa. Overall, our approach enables process designers to rapidly develop and update complex UI components in PAISs.

In the paper, an integrated approach for the modeling and enforcement of delegation policies in process-aware information systems is presented. In particular, a delegation extension for process-related role-based access control (RBAC) models is specified. The extension is generic in the sense that it can be used to extend process-aware information systems or process modeling languages with support for process-related RBAC delegation models. Moreover, the detection of delegation-related conflicts is discussed and a set of pre-defined resolution strategies for each potential conflict is provided. Thereby, the design-time and runtime consistency of corresponding RBAC delegation models can be ensured. Based on a formal metamodel, UML2 modeling support for the delegation of roles, tasks, and duties is provided. A corresponding case study evaluates the practical applicability of the approach with real-world business processes. Moreover, the approach is implemented as an extension to the BusinessActivity library and runtime engine.

Many present-day companies carry out a huge amount of daily operations through the use of their information systems without ever having done their own enterprise modeling. Business process mining is a well-proven solution which is used to discover the underlying business process models that are supported by existing information systems. Business process discovery techniques employ event logs as input, which are recorded by process-aware information systems. However, a wide variety of traditional information systems do not have any in-built mechanisms with which to collect events (representing the execution of business activities). Various mechanisms with which to collect events from non-process-aware information systems have been proposed in order to enable the application of process mining techniques to traditional information systems. Unfortunately, since business processes supported by traditional information systems are implicitly defined, correlating events into the appropriate process instance is not trivial. This challenge is known as the event correlation problem. This paper presents an adaptation of an existing event correlation algorithm and incorporates it into a technique in order to collect event logs from the execution of traditional information systems. The technique first instruments the source code to collect events together with some candidate correlation attributes. Based on several well-known design patterns, the technique provides a set of guidelines to support experts when instrumenting the source code. The event correlation algorithm is subsequently applied to the data set of events to discover the best correlation conditions, which are then used to create event logs. The technique has been semi-automated to facilitate its validation through an industrial case study involving a writer management system and a healthcare evaluation system. The study demonstrates that the technique is able to discover an appropriate correlation set and obtain well-formed event logs, thus enabling business process mining techniques to be applied to traditional information systems.

Process time patterns: A formal foundation

Compared to General Purpose Modeling Languages (GPMLs), Domain Specific Modeling Languages (DSMLs) have brought increasing expressivity and conciseness through the use of concepts and notations, which are customized by the characteristics of a specific problem domain. However, the creation of completely new languages can significantly increase software development costs. An alternative approach to creating new DSMLs refers to a customization of existing modeling languages. The DSML creation process through a customization of existing languages is a special case of Language Embedding. The embedding provides customization of an inherited infrastructure to a given domain. This paper elaborates a Domain-Specific Modeling environment for embedding an arbitrary DSML into an arbitrary GPML. The environment enables uniform development of DSMLs in the form of a lightweight extension of existing modeling languages.

Process aware information system (PAIS) is important in the recent business environment. Developments of PAIS need to consider contexts about technical and business elements. They are needed to develop PAIS effectively (e.g. monitoring environment and constructing adequate business process). Process mining is an important method for analyzing a business environment and utilizing PAIS development and improvement. LTL checking is an important method for checking a specific property to be satisfied with business processes, but correctly writing formal language like LTL is difficult. In this paper, we use LTL checking and prediction based on decision-tree learning for checking goal achievement, false detection and oversight detection. It helps writing properly LTL formula for representing the correct goal property. We conducted a case study using a real life log of traffic fine management process in Italy.

Business process modelling is an important part of system design. When designing or redesigning a business process, stakeholders specify, negotiate, and agree on business requirements to be satisfied, including non-functional requirements that concern the quality of the business process. This thesis addresses the question of how to specify and compute the quality of a business process, given the model that stakeholders use. The motivation for this thesis is the increasing importance of the quality of business processes. Knowing the quality of specific business processes enables stakeholders to judge if these processes need improvement. Knowing the quality of the constructs of those processes (viz., events, inputs, activities, and outputs) and the way they are structured enables a more detailed analysis of their shortcomings and provides a basis for the design of improvements. The research challenge of this thesis is grounded in the assumption that: “Organisations need an appropriate means to effectively compute achievement of their goals and objectives by their business processes.” Given this challenge, the main research question on which this thesis focuses is: “Can the quality of a business process be computed quantitatively at different levels of granularity?” The research objective is: “To develop frameworks, factors, and metrics for computing non-functional requirements (quality) of business processes quantitatively at different levels of granularity.” The outcomes of this thesis are: 1) BPIMM, a language-independent business process integrating meta-model, based on the concepts of seven mainstream business process modelling languages: BPMN, EPC, RAD, UML AD, SADT, IDEF0, and IDEF3. 2) BPC-QC (Business Process Concept - Quality Computation), an approach to quality computation at the lowest level of granularity of a business process. The approach consists of: i. BPC-QEF (Business Process Concept - Quality Evaluation Framework), a language-independent generic framework and algorithm to compute the quality of the constructs of a business process: event, input, activity, and output. ii. A set of business process quality dimensions and factors. The following quality dimensions are distinguished: performance, efficiency, reliability, recoverability, permissibility, and availability. Each dimension categorises different quality aspects in terms of factors. A non-exhaustive set of sixteen quantitative factors is provided. iii. Quality metrics for each of the quality factors, to facilitate a quantitative computation of the quality of a specific construct of a business process. 3) BP-QC (Business Process - Quality Computation), an approach to compute the quality at the highest level of granularity of a business process. The approach consists of: i. BP-CQCF (Business Process - Compositional Quality Computation Framework), a language-independent generic framework and algorithm to compute the quality of a business process as a whole, given the quality of its constructs. ii. A set of generic business process modelling patterns to decompose a business process into more succinct parts, namely: sequential, parallel with synchronisation, exclusive, inclusive, simple loop, and complex loop. iii. A set of over one hundred computational formulae. For each combination of modelling pattern and a quality factor, there is a formula to compute the quality. 4) AAV (Approach to Application and Validation), an evaluation plan to evaluate BPIMM, BPC-QC and BP-QC in practice, together with expert stakeholders. The plan consists of the units of measure, a measurement model, and a case study procedure. To evaluate the applicability of the contributions of this thesis to real world business needs, four case studies have been conducted in different environments: a Dutch educational institution, a global financial institution, an international financial service provider, and a Dutch research project on crisis management. Each of these case studies concerns a different, single business process. This thesis shows that: 1) A quality computation approach can be adopted independent of a business process modelling language. 2) Quantitative quality factors can be introduced specifically for the constructs of a business process. 3) Quantitative metrics and computational formulae can be developed for specific quality factors, allowing the computation of different aspects of the quality of a business process quantitatively at different levels of granularity. 4) An evaluation plan can be developed to evaluate the applicability of the contributions of this thesis (viz., BPIMM, BPC-QC, and BP-QC). The contributions of this thesis are designed to be beneficial to the areas of business and management, requirements engineering, software engineering, and business process modelling. In the areas of requirements engineering and software engineering, these contributions are intended to help practitioners to consider non-functional requirements at the earliest stage. In the area of business process modelling, information systems, service computing, and cloud computing, the contributions can be used for quality-driven modelling, design, and redesign. To conclude, knowing the quality value of a business process at different levels of granularity provides a basis for its improvement.

With the broad use of business process management technology, there are more and more business process models. Since the ability of different modelers is different, the quality of these models varies. A question arises here is that, can we refactor these models to improve the quality as practised in software engineering? Business process modeling can be regarded as declarative programming, and business process models can be used to drive the process aware information systems, which are generally developed with model driven architecture, so business process models are crucial for the efficiency of process aware information systems. In this paper, we propose a novel approach on how to systematically refactor business process models with parallel structures for sequence structures for the first time. More specifically, we analyze the real causal relations between business tasks based on data operation dependency analysis, and refactor business process models with process mining technology. After comprehensive model refactoring, parallel execution of business tasks can be maximized, so the efficiency of business processing can be improved, that is, the quality of business process models can be improved. Analysis and experiments show that our approach is effective and efficient.

Enhancing existing business process modeling languages with security concepts has attracted increased attention in research and several graphical notations and symbols have been proposed. How these extensions can be comprehended by users has not been evaluated yet. However, the comprehensibility of security concepts integrated within business process models is of utmost importance for many purposes such as communication, training, and later automation within a process-aware information system. If users do not understand the security concepts, this might lead to restricted acceptance or even misinterpretation and possible security problems in the sequel. In this paper, we evaluate existing security extensions of Business Process Model and Notation (BPMN) as BPMN constitutes the de facto standard in business modeling languages nowadays. The evaluation is conducted along two lines, i.e., a literature study and a survey. The findings of both evaluations identify shortcomings and open questions of existing approaches. This will yield the basis to convey security-related information within business process models in a comprehensible way and consequently, unleash the full effects of security modeling in business processes.

Companies are demanding more flexibility from their Process Aware Information Systems (PAIS). However, regulations and standards that impose limits to process executions are becoming increasingly important for business process management. The need for a compliance agenda and the security requisites for PAIS are pushing companies to search and to acquire new systems and technics for control and audit business processes. The aim is to avoid process execution that violates some business rules. In order to build an approach that support companies in auditing and controlling their business processes, there is a need for a formal and systematic modeling of business rules. In the present paper we have two objectives. The first one is to propose a set of business rules related to the ordering of tasks and to the involvement of a role or agent in cases. The second one is to build a supervisory control of PAIS that ensures compliance of business rules. To evaluate the correctness of our approach we applied it in two different business processes.KeywordsProcess-Aware Information Systembusiness rulessupervisory controlcompliancesecurity

The increasing adoption of process-aware information systems (PAISs) by enterprises has resulted in large process model collections. Usually, process models are created either by in-house domain experts or external consultants. Thereby, high model quality is crucial, i.e., process models should be syntactically correct and sound, and also reflect the real business processes properly. While numerous guidelines exist for creating correct and sound process models, there is only little work dealing with cognitive aspects affecting process modeling. This paper addresses this gap and presents a controlled experiment using construal level theory. We investigate the influence the social distance of a process designer to the modeled domain has on the creation of process models. In particular, we are able to show significant differences between high and low social distance in respect to model quality and granularity. The results may help enterprises to compose adequate teams for creating or optimizing business process models.

We present a break-glass extension for process-related role-based access control (RBAC) models. Our extension ensures the static (design-time) and dynamic (runtime) consistency of corresponding break-glass models. The extension is generic in the sense that it can, in principle, be used to extend arbitrary process-aware information systems or process modeling languages with support for process-related RBAC and corresponding break-glass policies. We implemented a library and runtime engine that provides full platform support for all properties of our approach.