Luisa Parody

Process Instance Query Language to Include Process Performance Indicators in DMN

Companies are increasingly incorporating commercial Business Process Management Systems (BPMSs) as mechanisms to automate their daily procedures. These BPMSs manage the information related to the instances that flow through the model (business data), and recover the information concerning the process performance (Process Performance Indicators). Process Performance Indicators (PPIs) tend to be used for the detection of possible deviations of expected behaviour, and help in the post-mortem analysis and redesign by improving the goals of the processes. However, not only are PPIs important in terms of their ability to measure and detect a derivation, but they should also be included at decision points to make the business processes more adaptable to the process reality at runtime. In this paper, we propose a complete solution that allows the incorporation of the PPIs into decision tasks, following the Decision Model and Notation (DMN) standard, with the aim of enriching the decisions that can be taken during the process execution. Our proposal firstly includes an extension of the decision rule grammar of the DMN standard, by incorporating the definition and the use of a Process Instance Query Language (PIQL) that offers information about the instances related to the PPIs involved. In order to achieve this objective, a framework has also been developed to support the enrichment of process instance query expressions (PIQEs). This framework combines a set of mature technologies to evaluate the decisions about PPIs at runtime. As an illustration a real sample has been used whose decisions are improved thanks to the incorporation of the PPIs at runtime.

Hybrid business process modeling for the optimization of outcome data

We propose the formalization of a hybrid model oriented towards obtaining the outcome data optimization, by combining a data-oriented declarative specification and a control-flow-oriented imperative specification.We propose the automatic creation from this hybrid model of an imperative model that is executable in a standard Business Process Management System.We defined an approach, based on the definition of a hybrid business process, which uses a constraint programming paradigm. For that, we define:the hybrid business process for the specification of the relationships between declarative data and control-flow imperative components of a business process.The automatic creation of an entirely imperative model at design time thanks to the use of Constraint Programming paradigm.The resulting imperative model is executable in any commercial Business Process Management System, and obtains, at execution time, the optimized outcome data of the process. Context: Declarative business processes are commonly used to describe permitted and prohibited actions in a business process. However, most current proposals of declarative languages fail in three aspects: (1) they tend to be oriented only towards the execution order of the activities; (2) the optimization is oriented only towards the minimization of the execution time or the resources used in the business process; and (3) there is an absence of capacity of execution of declarative models in commercial Business Process Management Systems.Objective: This contribution aims at taking into account these three aspects, by means of: (1) the formalization of a hybrid model oriented towards obtaining the outcome data optimization by combining a data-oriented declarative specification and a control-flow-oriented imperative specification; and (2) the automatic creation from this hybrid model to an imperative model that is executable in a standard Business Process Management System.Method: An approach, based on the definition of a hybrid business process, which uses a constraint programming paradigm, is presented. This approach enables the optimized outcome data to be obtained at runtime for the various instances.Results: A language capable of defining a hybrid model is provided, and applied to a case study. Likewise, the automatic creation of an executable constraint satisfaction problem is addressed, whose resolution allows us to attain the optimized outcome data. A brief computational study is also shown.Conclusion: A hybrid business process is defined for the specification of the relationships between declarative data and control-flow imperative components of a business process. In addition, the way in which this hybrid model automatically creates an entirely imperative model at design time is also defined. The resulting imperative model, executable in any commercial Business Process Management System, can obtain, at execution time, the optimized outcome data of the process.

Constraint-Driven Approach to Support Input Data Decision-Making in Business Process Management Systems

A business process consists of a set of activities that are performed in coordination in an organizational and technical environment (Weske 2007). The base of business process management systems (BPMS) is the explicit representation of business processes with their activities and the execution constraints between them. Compliance rules represent a natural step to include requirements between business functionality and data. For the design of a whole business process management (van der Aalst et al. 2003), it is necessary to design the model of activities and define the causal and temporal relationships between them (Walzer et al. 2008). Compliance rules can help to complete this information, since they can be used to validate business data (Chesani et al. 2008).

Extending BPMN 2.0 for Modelling the Combination of Activities That Involve Data Constraints

The combination of activities to achieve optimal goals sometimes has a complex solution. Business Process Model and Notation (BPMN) 2.0 facilitates the modelling of business processes by providing new artifacts, such as various types of tasks, source of data and relations between tasks. Sometimes, although the order of the activities can be known, the concrete data values that the activities interchange to optimize their behaviour needs to be found, specially when input parameters of an activity affect to the input parameter of the others. Taking into account the lack of priority and clear sequential relationship between the activities of such combination, a deep analysis of possible models and data input values for the activities is necessary. For that reason, an extension of BPMN 2.0 with a new type of sub-process and its associated marker is proposed. The aim of this new sub-process is to define, in an easy way, a combination of several activities to find out, in an automated way, the concrete values of the data handling that optimize an overall objective.

Prognosing the Compliance of Declarative Business Processes Using Event Trace Robustness

Several proposals have studied the compliance of execution of business process traces in accordance with a set of compliance rules. Unfortunately, the detection of a compliance violation (diagnosis) means that the observed events have already violated the compliance rules that describe the model. In turn, the detection of a compliance violation before its actual occurrence would prevent misbehaviour of the business processes. This functionality is referred to as proactive management of compliance violations in literature. However, existing approaches focus on the detection of inconsistencies between the compliance rules or monitoring process instances that are in a violable state. The notion of robustness could help us to prognosticate the occurrence of these inconsistent states in a premature way, and to detect, depending on the current execution state of the process instance, how “close” the execution is to a possible violation. On top of being able to possibly avoid violations, a robust trace is not sensitive to small changes. In this paper we propose the way to determine whether a process instance is robust against a set of compliance rules during its execution at runtime. Thanks to the use of constraint programming and the capacities of super solutions, a robust trace can be guaranteed.

Data-Oriented Declarative Language for Optimizing Business Processes

There is a significant number of declarative languages to describe business processes. They tend to be used when business processes need to be flexible and adaptable, being not possible to use an imperative description. Declarative languages in business process have been traditionally used to describe the order of activities, specifically the order allowed or prohibited. Unfortunately, none of them is worried about a declarative description of exchanged data between the activities and how they can influence the model. In this paper, we analyse the data description capacity of a variety of declarative languages in business processes. Using this analysis, we have detected the necessity to include data exchanged aspects in the declarative descriptions. In order to solve the gap, we propose a Data-Oriented Optimization Declarative LanguagE, called DOODLE, which includes the process requirements referred to data description, and the possibility to include an optimization function about the process output data.

PAIS-DQ: Extending process-aware information systems to support data quality in PAIS life-cycle

The successful execution of a Business Process implies to use data with an adequate level of quality, thereby enabling the output of processes to be obtained in accordance with users requirements. The necessity to be aware of the data quality in the business processes is known, but the problem is how the incorporation of data quality management can affect and increase the complexity of the software development that supports the business process life-cycle. In order to gain advantages that data quality management can provide, organizations need to introduce mechanisms aimed at checking whether data satisfies the established data-quality requirements. Desirably, the implementation, deployment and use of these mechanisms should not interfere into the regular working of the business processes. In order to enable this independence, we propose the PAIS-DQ framework as an extension of the classical Process-Aware Information System (PAIS) proposal. The PAIS-DQ addresses the concerns related to data quality management activities by minimizing the required time for the software developers. In addition, with the aim of guiding developers in the use of PAIS-DQ, a methodology has been also provided to facilitate organizations to deal with complex concerns. The methodology renders our proposal applicable in practice, and has been applied to a case study where a service architecture implementing the standard ISO/IEC 8000-100:2009 parts 100 to 140 is included.

CombiS-BP editor: Combining declarative and imperative languages in BP modelling: Demonstration paper

Business Process models allow business experts to describe the activities that must be performed to achieve a defined goal. Several imperative standard languages have been created to describe both control-flow and data-flow perspectives. Unfortunately, the imperative specification may be very difficult, complex and even inefficient to any kind of models, particularly, when these models depend on input data of each specific process instance. On the other hand, although business experts are able to define a declarative specification, they may be unaware of translating it into an imperative process model by using the existing standard languages. As a solution, we present CombiS-BP Editor, a tool that enables combined modelling of the two aforementioned specifications: (i) allows an imperative specification when experts know the execution order of the activities in the model and; (ii) enables a declarative specification when the experts know what has to be done instead of how it has to be done.