A System for Deduction-based Formal Verification of Workflow-oriented Software Models

The work concerns formal verification of workflow-oriented software models using deductive approach. The formal correctness of a model's behaviour is considered. Manually building logical specifications, which are considered as a set of temporal logic formulas, seems to be the significant obstacle for an inexperienced user when applying the deductive approach. A system, and its architecture, for the deduction-based verification of workflow-oriented models is proposed. The process of inference is based on the semantic tableaux method which has some advantages when compared to traditional deduction strategies. The algorithm for an automatic generation of logical specifications is proposed. The generation procedure is based on the predefined workflow patterns for BPMN, which is a standard and dominant notation for the modeling of business processes. The main idea for the approach is to consider patterns, defined in terms of temporal logic,as a kind of (logical) primitives which enable the transformation of models to temporal logic formulas constituting a logical specification. Automation of the generation process is crucial for bridging the gap between intuitiveness of the deductive reasoning and the difficulty of its practical application in the case when logical specifications are built manually. This approach has gone some way towards supporting, hopefully enhancing our understanding of, the deduction-based formal verification of workflow-oriented models.Comment: International Journal of Applied Mathematics and Computer Scienc

Propagating Changes between Declarative and Procedural Process Models

Debatt protseduuriliste ja deklaratiivsete keelte eeliste ja puuduste üle erinevate kasutusjuhtude korral on olnud tuline. Protseduurilised keeled on sobivamad operatiivsete protsesside modelleerimiseks, deklaratiivsed keeli kasutatakse regulatsioonide/juhiste jaoks. Ometi tekib olukordi, kus on mõistlik kombineerida neid keeli, et saavutada parem tulemus. Selle asemel, et sundida modelleerijaid õppima uusi hübriidkeeli, peame me paremaks kahe spetsifikatsiooni eraldi hoidmist ja pakume välja viisi, kuidas protseduurilist mudelit automaatselt muuta nii, et see oleks kooskõlas deklaratiivsete reeglitega. Nõudlus sellise lahenduse jaoks tekib, näiteks kui organisatsioon peab muutma protsesse vastavalt muutuvatele välistele reeglitele. Üldiselt on nii võimalik ära kasutada deklaratiivsete keelte paindlikust ja hoida kõrgetasemelist tuge, mida pakuvad protseduurilised keeled. Lisaks, võrreldes originaalset ja parandatud mudelit, on võimalik selgelt näha reeglite mõju. Käesolevas lõputöös sõnastame me antud probleemi, loome teoreetilise vundamendi ja pakume välja olekumasinatel põhineva lahenduse, mida me võrdleme olemasolevate lahendustega mudelite parandamiseks ja protsesside avastamiseks.The debate on advantages and disadvantages of declarative versus procedural process modelling languages for different usage scenarios has been intense. Procedural languages are more suited for describing operational processes while declarative ones for expressing regulations/guidelines, and in many situations the need of combining the benefits of the two rises. Instead of forcing modellers to use a hybrid language, we envisage to keep the two specifications separate and propose a technique that automatically adapts procedural models so as to comply with sets of declarative rules. This not only fits scenarios where, e.g., company processes have to be modified according to changing external rules, but, more in general, it presents a way to take advantage of the flexibility of declarative while maintaining the high level of support provided by procedural languages. Furthermore, by comparing the original and the resulting procedural models, the impact of rules is clearly exposed. In this thesis, we frame the problem above by providing its theoretical characterisation and propose an automata-based solution, which is then evaluated against approaches leveraging state-of-the-art techniques for process discovery and model repair

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

UnconstrainedMiner : efficient discovery of generalized declarative process models

Process discovery techniques derive a process model from observed behavior (e.g., event logs). In case of less structured processes, declarative models have notable advantages over procedural models. A declarative model consists of a set of temporal constraints over the activities in the event log. In this paper, we address three limitations of current discovery techniques: their unclear semantics of declarative constraints for business processes, their non-performative discovery of constraints, and their potential identification of vacuous constraints. We implemented our contributions as a declarative discovery algorithm for the Declare language. Our evaluations on a real-life event log indicate that it outperforms state of the art techniques by several orders of magnitude

Automatic Generation of Optimized Process Models from Declarative Specifications

Process models often are generic, i. e., describe similar cases or contexts. For instance, a process model for commissioning can cover both vehicles with an automatic and with a manual transmission, by executing alternative tasks. A generic process model is not optimal compared to one tailored to a specific context. Given a declarative specification of the constraints and a specific context, we study how to automatically generate a good process model and propose a novel approach. We focus on the restricted case that there are not any repetitions of a task, as is the case in commissioning and elsewhere, e. g., manufacturing. Our approach uses a probabilistic search to find a good process model according to quality criteria. It can handle complex real-world specifications containing several hundred constraints and more than one hundred tasks. The process models generated with our scheme are superior (nearly twice as fast) to ones designed by professional modelers by hand

A Conceptual Framework for Adapation

This paper presents a white-box conceptual framework for adaptation that promotes a neat separation of the adaptation logic from the application logic through a clear identification of control data and their role in the adaptation logic. The framework provides an original perspective from which we survey archetypal approaches to (self-)adaptation ranging from programming languages and paradigms, to computational models, to engineering solutions

A Conceptual Framework for Adapation

This paper presents a white-box conceptual framework for adaptation that promotes a neat separation of the adaptation logic from the application logic through a clear identification of control data and their role in the adaptation logic. The framework provides an original perspective from which we survey archetypal approaches to (self-)adaptation ranging from programming languages and paradigms, to computational models, to engineering solutions

A Conceptual Framework for Adapation

We present a white-box conceptual framework for adaptation. We called it CODA, for COntrol Data Adaptation, since it is based on the notion of control data. CODA promotes a neat separation between application and adaptation logic through a clear identification of the set of data that is relevant for the latter. The framework provides an original perspective from which we survey a representative set of approaches to adaptation ranging from programming languages and paradigms, to computational models and architectural solutions