Combi-BP: automating the data-oriented optimization in business processes. From declarative to executable models.

One of the main objectives of a business expert is to model the business goals of an enterprise process. Several languages have been created to describe the necessary activities to achieve the objective, especially in the business process context. These languages can be divided into imperative and declarative ones. Declarative languages tend to be used when the speci c model is unknown, being possible to describe what has to be done instead of how. Otherwise, imperative languages permit to describe how the things have to be done and then, the imperative models can be executed in any Business Process Management System (BPMS). The declarative descriptions are more exible, since they permit to describe the model in a more relaxed way, which means that various process executions can follow the same declarative description. However, both paradigms are focused on the activities order description, but unfortunately, the data perspective is missed. Furthermore, the optimization of a business goal which depends on the exchanged data during the execution of the business process has not been included in previous proposals. There are no solutions that allow the business experts to describe nor execute a declarative description where the executed model depends on the exchanged data between the involved activities in each instance. In this thesis dissertation, an approach to support this data-oriented optimization in business process is presented. A data-oriented optimization problem is a process whose main purpose is to obtain the best business product. In order to obtain this business product, the process must combine several activities by taking into account the existing data-structure and data-value dependencies. Both kind of dependencies are established by a set of constraints that relate the data (consumed and provided by the activities) and the data given by the customer. Therefore, the BPs under the scope of our research are those which are centred on developing sound data in business processes, analysing how data-structure and data-value dependencies can aect the correct business process execution. However, if the data provided at runtime for the activities that conform the model have not got enough level of quality, then business process will not be successfully executed. The base of the proposal is focused on the combination of the advantages of both paradigms: the exibility of the declaratives, and the automatic execution in a BPMS of the imperatives. On the one hand, we want to describe a exible model using a declarative description where the exchanged data and an optimization objective are included. In the other hand, this declarative model must be executed in a generic business process management system with the aim of support any instance of the process. Therefore, how the declarative description can be transformed into an imperative business process is developed. The transformation methodology that we propose is based on Model-Driven Architecture. Firstly, the declarative is transformed into an imperative which takes into account the data-structure dependencies. The exibility of the declarative speci cation is kept thanks to the use of Constraint Programming. On the other hand, the resulting imperative model is enriched with new intelligent techniques, also based on Constraint Programming, in order to solve the data-value dependencies. Finally, a methodology and an implementation are developed in order to make the business process aware of the data-quality aspects

Business Process Configuration According to Data Dependency Specification

Configuration techniques have been used in several fields, such as the design of business process models. Sometimes these models depend on the data dependencies, being easier to describe what has to be done instead of how. Configuration models enable to use a declarative representation of business processes, deciding the most appropriate work-flow in each case. Unfortunately, data dependencies among the activities and how they can affect the correct execution of the process, has been overlooked in the declarative specifications and configurable systems found in the literature. In order to find the best process configuration for optimizing the execution time of processes according to data dependencies, we propose the use of Constraint Programming paradigm with the aim of obtaining an adaptable imperative model in function of the data dependencies of the activities described declarative.Ministerio de Ciencia y Tecnología TIN2015-63502-C3-2-RFondo Europeo de Desarrollo Regiona

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).Junta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Towards the Detection of Promising Processes by Analysing the Relational Data

Business process discovery provides mechanisms to extract the general process behaviour from event observations. However, not always the logs are available and must be extracted from repositories, such as relational databases. Derived from the references that exist between the relational tables, several are the possible combinations of traces of events that can be extracted from a relational database. Dif ferent traces can be extracted depending on which attribute represents the case−id, what are the attributes that represent the execution of an activity, or how to obtain the timestamp to define the order of the events. This paper proposes a method to analyse a wide range of possible traces that could be extracted from a relational database, based on measuring the level of interest of extracting a trace log, later used for a discov ery process. The analysis is done by means of a set of proposed metrics before the traces are generated and the process is discovered. This anal ysis helps to reduce the computational cost of process discovery. For a possible case−id every possible traces are analysed and measured. To validate our proposal, we have used a real relational database, where the detection of processes (most and least promising) are compared to rely on our proposal.Ministerio de Ciencia y Tecnología RTI2018-094283-B-C3

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.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Contract-based Diagnosis for Business Process Instances using Business Compliance Rules

In order to increase the quality of business pro cesses when they are automated, the correctness of the activities can be checked by means of an analysis of the corresponding business compli ance rules. By analyzing the trace of an instance of a business process, it is possible to detect the correctness of the process and to determine which activity is faulty. Each activity or set of activities is related to a set of business compliance rules, which work as contracts that the activities must satisfy throughout the dataflow. In order to diagnose a business process instance, not all the activities participate in every single execution, since there are control flows that per mit the execution of several branches for a varied number of times. We propose to automate the di agnosis of these executions of a business process taking into account the involved activities and their business compliance rules. Our main contri butions are related to the construction of the cor responding framework using several techniques related to the constraint programming paradigm to obtain the incorrect activities. The two differ ent proposals consider the tradeoff between the obtaining of the minimal diagnosis and the per formanceJunta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Using Distributed CSPs to Model Business Processes Agreement in Software Multiprocess

A business process consists of a set of activities which are performed in a coordination way to obtain an objective. Sometimes the definition of this objective using only a classic business processes management is not possible. When the choreography of the processes cannot be defined with a combination of tasks using sequences, conditions, ’xor’, ’or’ and ’split’ control flow patterns, another representation and solution are necessary to be used. This problem makes difficult the decision making in software management projects. In this paper a way to describe a process agreement is described where the execution and the number of tasks execution order of the Web Services cannot be defined. As a case study, the resource distribution in a multiproject development environment is used. In this case, the processes have to achieve an agreement in function of the business rules that relate the processes. In order to achieve this objective, the Distributed Constraint Satisfaction Problems are used to model and solve this type of problemsJunta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Hybrid business process modeling for the optimization of outcome data

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.Ministerio de Ciencia y Tecnología TIN2009-1371

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