Artem Polyvyanyy

Artem Polyvyanyy
University of Melbourne | MSD · Department of Computing and Information Systems

Dr. rer. nat. (PhD)

About

122
Publications
30,684
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
2,318
Citations
Introduction
Dr. Artem Polyvyanyy is a senior lecturer at the School of Computing and Information Systems, Faculty of Engineering and Information Technology, at the University of Melbourne (Australia). He has a strong background in Theoretical Computer Science, Software Engineering, and Business Process Management from the National University of Kyiv-Mohyla Academy (Ukraine), Hasso Plattner Institute (Germany), and the University of Potsdam (Germany).
Additional affiliations
March 2018 - present
University of Melbourne
Position
  • Professor (Associate)
January 2015 - March 2018
Queensland University of Technology
Position
  • Lecturer
April 2012 - January 2015
Queensland University of Technology
Position
  • Research Associate

Publications

Publications (122)
Article
Full-text available
Substantial research efforts have been expended to deal with the complexity of concurrent systems that is inherent to their analysis, e.g., works that tackle the well-known state space explosion problem. Approaches differ in the classes of properties that they are able to suitably check and this is largely a result of the way they balance the trade...
Conference Paper
Full-text available
The design of concurrent software systems, in particular process-aware information systems, involves behavioral modeling at various stages. Recently, approaches to behavioral analysis of such systems have been based on declarative abstractions defined as sets of behavioral relations. However, these relations are typically defined in an ad-hoc manne...
Conference Paper
Full-text available
Process-Aware Information Systems (PAISs) support executions of operational processes that involve people, resources, and software applications on the basis of process models. Process models describe vast, often infinite, amounts of process instances, i.e., workflows supported by the systems. With the increasing adoption of PAISs, large process mod...
Conference Paper
Full-text available
There are many use cases in business process management that require the comparison of behavioral models. For instance, verifying equivalence is the basis for assessing whether a technical workflow correctly implements a business process, or whether a process realization conforms to a reference process. This paper proposes an equivalence relation f...
Conference Paper
Full-text available
A business process is often modeled using some kind of a directed flow graph, which we call a workflow graph. The Refined Process Structure Tree (RPST) is a technique for workflow graph parsing, i.e., for discovering the structure of a workflow graph, which has various applications. In this paper, we provide two improvements to the RPST. First, we...
Conference Paper
Process mining extracts value from the traces recorded in the event logs of IT-systems, with process discovery the task of inferring a process model for a log emitted by some unknown system. Generalization is one of the quality criteria applied to process models to quantify how well the model describes future executions of the system. Generalizatio...
Article
State-of-the-art process discovery methods construct free-choice process models from event logs. Consequently, the constructed models do not take into account indirect dependencies between events. Whenever the input behaviour is not free-choice, these methods fail to provide a precise model. In this paper, we propose a novel approach for enhancing...
Chapter
This chapter gives a brief introduction to the research area of process querying. Concretely, it articulates the motivation and aim of process querying, gives a definition of process querying, presents the core artifacts studied in process querying, and discusses a framework for guiding the design, implementation, and evaluation of methods for proc...
Chapter
A processProcess is a collection of actions that were already, are currently being, or must be taken in order to achieve a goal, where an actionAction is an atomic unit of work, for instance, a business activity or an instruction of a computer program. A process repositoryProcessrepository is an organized collection of models that describe processe...
Chapter
Process querying studies concepts and methods from fields like Big data, process modeling and analysis, business process intelligence, and process analytics and applies them to retrieve and manipulate real-world and designed processes. This chapter reviews state-of-the-art methods for process querying, summarizes techniques used to implement proces...
Article
There are many fields of computing in which having access to large volumes of data allows very precise models to be developed. For example, machine learning employs a range of algorithms that deliver important insights based on analysis of data resources. Similarly, process mining develops algorithms that use event data induced by real-world proces...
Chapter
Process analytics is an umbrella of data-driven techniques which includes making predictions for individual process instances or overall process models. At the instance level, various novel techniques have been recently devised, tackling next activity, remaining time, and outcome prediction. At the model level, there is a notable void. It is the am...
Chapter
Full-text available
Process models automatically discovered from event logs represent business process behavior in a compact graphical way. To compare process variants, e.g., to explore how the system’s behavior changes over time or between customer segments, analysts tend to visually compare conceptual process models discovered from different “slices” of the event lo...
Article
Robotic Process Automation (RPA) is a technology to automate routine work such as copying data across applications or filling in document templates using data from multiple applications. RPA tools allow organizations to automate a wide range of routines. However, identifying and scoping routines that can be automated using RPA tools is time consumi...
Conference Paper
Full-text available
The behavioural comparison of systems is an important concern of software engineering research. For example, the areas of specification discovery and specification mining are concerned with measuring the consistency between a collection of execution traces and a program specification. This problem is also tackled in process mining with the help of...
Conference Paper
Full-text available
This paper presents the idea of a compendium of process technologies, i.e., a concise but comprehensive collection of techniques for process model analysis that support research on the design, execution, and evaluation of processes. The idea originated from observations on the evolution of process-related research disciplines. Based on these observ...
Article
Full-text available
In the Agent-Based Modeling (ABM) paradigm, an organization is a Multi-Agent System (MAS) composed of autonomous agents inducing business processes. Process Mining automates the creation, update, and analysis of explicit business process models based on event data. Process Mining techniques make simplifying assumptions about the processes discovere...
Preprint
Full-text available
Process mining studies ways to derive value from process executions recorded in event logs of IT-systems, with process discovery the task of inferring a process model for an event log emitted by some unknown system. One quality criterion for discovered process models is generalization. Generalization seeks to quantify how well the discovered model...
Preprint
Full-text available
State-of-the-art process discovery methods construct free-choice process models from event logs. Consequently, the constructed models do not take into account indirect dependencies between events. Whenever the input behaviour is not free-choice, these methods fail to provide a precise model. In this paper, we propose a novel approach for enhancing...
Preprint
Robotic Process Automation (RPA) is a technology to automate routine work such as copying data across applications or filling in document templates using data from multiple applications. RPA tools allow organizations to automate a wide range of routines. However, identifying and scoping routines that can be automated using RPA tools is time consumi...
Chapter
The aim of a process discovery algorithm is to construct from event data a process model that describes the underlying, real-world process well. Intuitively, the better the quality of the input event data, the better the quality of the resulting discovered model should be. However, existing process discovery algorithms do not guarantee this relatio...
Chapter
Full-text available
This paper addresses the challenge of decoupling “back-office” enterprise system functions in order to integrate them with the Industrial Internet-of-Things (IIoT). IIoT is a widely anticipated strategy, combining IoT technologies managing physical object movements, interactions and contexts, with business contexts. However, enterprise systems, sup...
Article
Full-text available
Robotic process automation (RPA) is an emerging technology that allows organizations automating repetitive clerical tasks by executing scripts that encode sequences of fine-grained interactions with Web and desktop applications. Examples of clerical tasks include opening a file, selecting a field in a Web form or a cell in a spreadsheet, and copy-p...
Preprint
Full-text available
Process analytics is the field focusing on predictions for individual process instances or overall process models. At the instance level, various novel techniques have been recently devised, tackling next activity, remaining time, and outcome prediction. At the model level, there is a notable void. It is the ambition of this paper to fill this gap....
Article
Initially, process mining focused on discovering process models from event data, but in recent years the use and importance of conformance checking has increased. Conformance checking aims to uncover differences between a process model and an event log. Many conformance checking techniques and measures have been proposed. Typically, these take into...
Article
Full-text available
Conformance checking is an area of process mining that studies methods for measuring and characterizing commonalities and discrepancies between processes recorded in event logs of IT-systems and designed processes, either captured in explicit process models or implicitly induced by information systems. Applications of conformance checking range fro...
Article
Event sequence data is increasingly available in various application domains, such as business process management, software engineering, or medical pathways. Processes in these domains are typically represented as process diagrams or flow charts. So far, various techniques have been developed for automatically generating such diagrams from event se...
Book
This book constitutes the thoroughly refereed proceedings of the international workshops associated with the 33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021, which was held during June 28-July 2, 2021. The conference was planned to take place in Melbourne, Australia, but changed to an online format due to the C...
Preprint
The aim of a process discovery algorithm is to construct from event data a process model that describes the underlying, real-world process well. Intuitively, the better the quality of the event data, the better the quality of the model that is discovered. However, existing process discovery algorithms do not guarantee this relationship. We demonstr...
Chapter
Full-text available
Modern software systems are often built using service-oriented principles. Atomic components, be that web-or microservices, allow constructing flexible and loosely coupled systems. In such systems, services are building blocks orchestrated by business processes the system supports. Due to the complexity and heterogeneity of industrial software syst...
Preprint
Full-text available
Event sequence data is increasingly available in various application domains, such as business process management, software engineering, or medical pathways. Processes in these domains are typically represented as process diagrams or flow charts. So far, various techniques have been developed for automatically generating such diagrams from event se...
Conference Paper
Full-text available
Robotic Process Automation (RPA) is a technology to develop software bots that automate repetitive sequences of interactions between users and software applications (a.k.a. routines). To take full advantage of this technology, organizations need to identify and to scope their routines. This is a challenging endeavor in large organizations, as routi...
Conference Paper
Full-text available
Given an event log as a collection of recorded real-world process traces, process mining aims to automatically construct a process model that is both simple and provides a useful explanation of the traces. Conformance checking techniques are then employed to characterize and quantify commonalities and discrepancies between the log's traces and the...
Conference Paper
Full-text available
This paper proposes an approach to analyze an event log of a business process in order to generate case-level recommendations of treatments that maximize the probability of a given outcome. Users classify the attributes in the event log into controllable and non-controllable, where the former correspond to attributes that can be altered during an e...
Preprint
This paper proposes an approach to analyze an event log of a business process in order to generate case-level recommendations of treatments that maximize the probability of a given outcome. Users classify the attributes in the event log into controllable and non-controllable, where the former correspond to attributes that can be altered during an e...
Chapter
Full-text available
A plethora of algorithms for automatically discovering process models from event logs has emerged. The discovered models are used for analysis and come with a graphical flowchart-like representation that supports their comprehension by analysts. According to the Occam’s Razor principle, a model should encode the process behavior with as few constru...
Preprint
Full-text available
This paper presents a command-line tool, called Entropia, that implements a family of conformance checking measures for process mining founded on the notion of entropy from information theory. The measures allow quantifying classical non-deterministic and stochastic precision and recall quality criteria for process models automatically discovered f...
Preprint
Robotic Process Automation (RPA) is a technology to develop software bots that automate repetitive sequences of interactions between users and software applications (a.k.a. routines). To take full advantage of this technology, organizations need to identify and to scope their routines. This is a challenging endeavor in large organizations, as routi...
Preprint
Full-text available
Given an event log as a collection of recorded real-world process traces, process mining aims to automatically construct a process model that is both simple and provides a useful explanation of the traces. Conformance checking techniques are then employed to characterize and quantify commonalities and discrepancies between the log's traces and the...
Chapter
According to our recent proposal, an information system is a combination of a process model captured as a Petri Net with Identifiers, an information model specified in the first-order logic over finite sets with equality, and a specification of how the transitions in the net manipulate information facts. The Information Systems Modeling (ISM) Suite...
Chapter
State-of-the-art process discovery methods construct free-choice process models from event logs. Hence, the constructed models do not take into account indirect dependencies between events. Whenever the input behavior is not free-choice, these methods fail to provide a precise model. In this paper, we propose a novel approach for the enhancement of...
Chapter
Business process management (BPM) aims to support changes and innovations in organizations’ processes. Process mining complements BPM with methods, techniques, and tools that provide insights based on observed executions of business processes recorded in event logs of information systems. State-of-the-art discovery and conformance techniques comple...
Chapter
This paper addresses the challenge of automated remodularization of large systems as microservices. It focuses on the analysis of enterprise systems, which are widely used in corporate sectors and are notoriously large, monolithic and challenging to manually decouple because they manage asynchronous, user-driven business processes and business obje...
Article
Full-text available
The behavioural comparison of systems is an important concern of software engineering research. For example, the areas of specification discovery and specification mining are concerned with measuring the consistency between a collection of execution traces and a program specification. This problem is also tackled in process mining with the help of...
Conference Paper
Full-text available
The problem of probabilistic goal recognition consists of automatically inferring a probability distribution over a range of possible goals of an autonomous agent based on the observations of its behavior. The state-of-the-art approaches for probabilistic goal recognition assume the full knowledge about the world the agent operates in and possible...
Conference Paper
Full-text available
This paper addresses the challenge of automated remodularization of large systems as microservices. It focuses on the analysis of enterprise systems, which are widely used in corporate sectors and are notoriously large, monolithic and challenging to manually decouple because they manage asynchronous, user-driven business processes and business obje...
Article
Full-text available
Process models constitute valuable artifacts for organizations. A process model formally captures the way an organization works internally and interacts with its customers and partners. Over time, more models may be created as business practices evolve (leading to different versions of models) or an organization expands, e.g., through mergers or ac...
Conference Paper
Full-text available
According to our recent proposal, an information system is a combination of a process model captured as a Petri Net with Identifiers, an information model specified in the first-order logic over finite sets with equality, and a specification of how the transitions in the net manipulate information facts. The Information Systems Modeling (ISM) Suite...
Conference Paper
Full-text available
State-of-the-art process discovery methods construct free-choice process models from event logs. Hence, the constructed models do not take into account indirect dependencies between events. Whenever the input behavior is not free-choice, these methods fail to provide a precise model. In this paper, we propose a novel approach for the enhancement of...
Conference Paper
Full-text available
Business process management (BPM) aims to support changes and innovations in organizations' processes. Process mining complements BPM with methods, techniques, and tools that provide insights based on observed executions of business processes recorded in event logs of information systems. State-of-the-art discovery and conformance techniques comple...
Preprint
Full-text available
Robotic Process Automation (RPA) is a technology for automating repetitive routines consisting of sequences of user interactions with one or more applications. In order to fully exploit the opportunities opened by RPA, companies need to discover which specific routines may be automated, and how. In this setting, this paper addresses the problem of...
Conference Paper
Full-text available
This paper presents Robidium: a tool that discovers automatable routine tasks from User Interactions (UI) logs and generates Robotic Process Automation (RPA) scripts to automate such routines. Unlike record-and-replay features provided by commercial RPA tools, Robidium may take as input an UI log that is not specifically recorded to capture a pre-i...
Conference Paper
Full-text available
Research on concept drift detection has inspired recent advancements of process mining and expanding the growing arsenal of process analysis tools. What has so far been missing in this new research stream are techniques that support comprehensive process drift analysis in terms of localizing, drilling down, quantifying, and visualizing process drif...
Article
Full-text available
Automated process discovery techniques enable users to generate business process models from event logs extracted from enterprise information systems. Traditional techniques in this field generate procedural process models (e.g., in the BPMN notation). When dealing with highly variable processes, the resulting procedural models are often too comple...
Chapter
Full-text available
Microservices have been introduced to industry as a novel architectural design for software development in cloud-based applications. This development has increased interest in finding new methodologies to migrate existing enterprise systems into microservices to achieve desirable performance characteristics such as high scalability, high availabili...
Article
Full-text available
The paper at hand motivates, proposes, demonstrates, and evaluates a novel systematic approach to discovering causal dependencies between events encoded in large arrays of data, called causality mining. The approach has emerged in the discussions with our project partner, an Australian public energy company. It was successfully evaluated in a case...
Chapter
Full-text available
Recent research has introduced ideas from concept drift into process mining to enable the analysis of changes in business processes over time. This stream of research, however, has not yet addressed the challenges of drift categorization, drilling-down, and quantification. In this paper, we propose a novel technique for managing process drifts, cal...
Chapter
Full-text available
A key impediment towards maturing microservice architecture conceptions is the uncertainty about what it means to design fine-grained functionality for microservices. Under a traditional service-oriented architecture (SOA), the unit of functionality for software components concerns individual business domain objects and encapsulated operations, ena...
Preprint
Full-text available
Organizations can benefit from the use of practices, techniques, and tools from the area of business process management. Through the focus on processes, they create process models that require management, including support for versioning, refactoring and querying. Querying thus far has primarily focused on structural properties of models rather tha...
Preprint
Full-text available
Organizations can benefit from the use of practices, techniques, and tools from the area of business process management. Through the focus on processes, they create process models that require management, including support for versioning, refactoring and querying. Querying thus far has primarily focused on structural properties of models rather tha...
Conference Paper
Full-text available
Recent research has introduced ideas from concept drift into process mining to enable the analysis of changes in business processes over time. This stream of research, however, has not yet addressed the challenges of drift categoriza-tion, drilling-down, and quantification. In this tool demonstration paper, we present a novel software tool to analy...