300 research outputs found

    Platform Architecture for the Diagram Assessment Domain

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    Using e-learning and e-assessment environments in higher education bears considerable potential for both students and teachers. In this contribution we present an architecture for a comprehensive e-assessment platform for the modeling domain. The platform – currently developed in the KEA-Mod project – features a micro-service architecture and is based on different inter-operable components. Based on this idea, the KEA-Mod platform will provide e-assessment capabilities for various graph-based modeling languages such as Unified Modeling Language (UML), EntityRelationship diagrams (ERD), Petri Nets, Event-driven Process Chains (EPC) and the Business Process Model and Notation (BPMN) and their respective diagram types

    Extensible Workflow Engine With Support for Adaptable Business Process Management

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    Predmet istraživanja disertacije pripada oblasti softverskog inženjerstva i poslovnih procesa, odnosno upravljanja poslovnim procesima. Upravljenje poslovnim procesima pripada oblasti koja je izuzetno dinamična kako u pogledu rasta zahteva i očekivanja sa kojima se suočava sa jedne strane, tako i novih pristupa i tehnologija koji pokušavaju da premoste i reše uočene probleme sa druge strane. Modeli procesa, podataka, kao i alati na kojima su zasnovani procesno orijentisani informacioni sistemi imaju zadatak da obezbede kontrolisano upravljanje i predvidivo izvršavanje poslovnih procesa. Osnovna premisa za funkcionisanje ovakvih sistema je da poslovna funkcija može biti predstavljena kao proces i/ili radni tok – orkestrirani lanac aktivnosti (zadataka), koji kada se izvrše u definisanom redosledu daju uspešan ishod procesa. Prilagođavanje promenama u jednom poslovnom procesu je postala jedna od najznačajnijih aktivnosti u savremenim poslovnim informacionim sistemima. Međutim, efikasna primena ove aktivnosti u kontekstu savremenih poslovnih procesno- orijentisanih sistema je donekle ograničena načinima implementacije samih procesnih sistema, koji najčešće prave striktnu distinkciju između modela procesa i instanci kreiranih na osnovu takvog modela. Ovakva implementacija, iako potpuno validna i široko prihvaćena, ipak ima i veliki nedostatak – slabu mogućnost adaptacije već pokrenutih instanci procesa na nove okolnosti, koje se mogu reflektovati na neophodne izmene u samom procesu. Redizajniranje, usaglašavanje i potvrđivanje validnosti i izmenjenog modela procesa, i implementacija nove verzije i dalje je daleko brži postupak nego izmena logike ugrađene u sam kod aplikacije. Cilj ove disertacije, na osnovu pomenutog, je kreiranje tehničkog rešenja koje će pružati podršku za adaptabilnost procesa u procesno- orijentisanim poslovnim sistemima, kao i odgovor na pitanje, kako i u kojoj meri je moguće primeniti adaptabilnost na tekućim procesima u procesno orijentisanim poslovnim sistemima. Dva problema u značajnoj meri utiču na usvajanje adaptabilnih procesno- orijentisanih poslovnih sistema. Prvi problem se odnosi na kompleksnost ove aktivnosti. Izmena modela procesa i kreiranje nove verzije koja će se koristiti za buduće instance je postupak koji je uobičajen, dobro poznat i u širokoj upotrebi. Ali adaptacija koja se propagira trenutno i na već pokrenute instance procesa nosi mnogo više nepoznanica i potencijalnih problema. Neophodno je sagledati trenutno stanje izvršavanja svake pojedine instance, izvršiti evaluaciju primenjivosti u kontekstu svake od tih instanci. Potrebno znanje za primenjivanje ovakvog pristupa, odnosno kreiranje rešenja sa podrškom za adaptabilnost procesa podrazumeva i mogućnost analitičkog sagledavanja posledica koje takva izmena može imati na procesne instance koje se već izvršavaju. Neophodno je dosta iskustva kako bi se sa sigurnošću predvidelo da li implementacija neke nove promene u već pokrenutoj instanci ne dovodi u pitanje samo izvršavanje procesa. Procesna okruženja koja podržavaju adaptabilnost bi stoga trebala da pruže alat koji omogućava da se ove provere sprovedu pre nego što do neželjenih posledica dođe. Drugi problem nastaje zbog nedostatka postojanja konkretne paradigme koja bi opisala način primene ove aktivnosti, odnosno slučajevi koji zahtevaju primenu adaptabilnosti se razlikuju i specifični su u zavisnosti od ciljanog poslovnog sistema. Cilj ove disertacije, na osnovu pomenutog, je kreiranje tehničkog rešenja koje će pružati podršku za adaptabilnost procesa u procesno- orijentisanim poslovnim sistemima, kao i odgovor na pitanje, kako i u kojoj meri je moguće primeniti adaptabilnost na tekućim procesima u procesno orijentisanim poslovnim sistemima.Research topic of this dissertation is from the area of software engineering and business processes and business process management. An ever-increasing demand for information systems in the last few decades brought many new opportunities but also presented new challenges for companies in the landscape of doing business globally. In these terms, software systems need to adapt almost instantaneously to new requirements, opportunities, and customer expectations. Process-aware systems have become integral part in business information system solutions, finding their place at different locations. Process and data models, as well as tools on which process-oriented information systems are based, have the task of ensuring controlled management and predictable execution of business processes. The basic premise for the functioning of such systems is that the business function can be represented as a process and/or workflow - an orchestrated chain of activities (tasks), which when performed in a defined sequence, give a successful process outcome. Adapting to changes in a business process has become one of the most important activities in modern business information systems. However, the effective application of this activity in the context of modern business assessment-oriented systems is somewhat limited by the implementation methods of the process systems themselves, which usually make a strict distinction between process models and instances created on the basis of such models. Two problems significantly affect the adoption of adaptable process-oriented business systems. The first problem is related to the complexity of this activity. Modifying a process model and creating a new version to be used for future instances is a procedure that is common, well-known, and widely used. But the adaptation that propagates currently and to already started instances of the process carries many more unknowns and potential problems. It is necessary to look at the current state of execution of each individual instance, to evaluate the applicability in the context of each of those instances. A lot of experience is necessary in order to predict with certainty whether the implementation of a new change in an already started instance does not call into question the execution of the process itself. Process environments that support adaptability should therefore provide tools that enable these checks to be carried out before unintended consequences occur. Another problem arises due to the lack of existence of a concrete paradigm that would describe the way of applying this activity, that is, the cases that require the application of adaptability differ and are specific depending on the targeted business system. The goal of this dissertation, based on the aforementioned, is to create a technical solution that will provide support for process adaptability in processoriented business systems, as well as an answer to the question of how and to what extent it is possible to apply adaptability to ongoing processes in process-oriented business systems

    Extensible Workflow Engine With Support for Adaptable Business Process Management

    Get PDF
    Predmet istraživanja disertacije pripada oblasti softverskog inženjerstva i poslovnih procesa, odnosno upravljanja poslovnim procesima. Upravljenje poslovnim procesima pripada oblasti koja je izuzetno dinamična kako u pogledu rasta zahteva i očekivanja sa kojima se suočava sa jedne strane, tako i novih pristupa i tehnologija koji pokušavaju da premoste i reše uočene probleme sa druge strane. Modeli procesa, podataka, kao i alati na kojima su zasnovani procesno orijentisani informacioni sistemi imaju zadatak da obezbede kontrolisano upravljanje i predvidivo izvršavanje poslovnih procesa. Osnovna premisa za funkcionisanje ovakvih sistema je da poslovna funkcija može biti predstavljena kao proces i/ili radni tok – orkestrirani lanac aktivnosti (zadataka), koji kada se izvrše u definisanom redosledu daju uspešan ishod procesa. Prilagođavanje promenama u jednom poslovnom procesu je postala jedna od najznačajnijih aktivnosti u savremenim poslovnim informacionim sistemima. Međutim, efikasna primena ove aktivnosti u kontekstu savremenih poslovnih procesno- orijentisanih sistema je donekle ograničena načinima implementacije samih procesnih sistema, koji najčešće prave striktnu distinkciju između modela procesa i instanci kreiranih na osnovu takvog modela. Ovakva implementacija, iako potpuno validna i široko prihvaćena, ipak ima i veliki nedostatak – slabu mogućnost adaptacije već pokrenutih instanci procesa na nove okolnosti, koje se mogu reflektovati na neophodne izmene u samom procesu. Redizajniranje, usaglašavanje i potvrđivanje validnosti i izmenjenog modela procesa, i implementacija nove verzije i dalje je daleko brži postupak nego izmena logike ugrađene u sam kod aplikacije. Cilj ove disertacije, na osnovu pomenutog, je kreiranje tehničkog rešenja koje će pružati podršku za adaptabilnost procesa u procesno- orijentisanim poslovnim sistemima, kao i odgovor na pitanje, kako i u kojoj meri je moguće primeniti adaptabilnost na tekućim procesima u procesno orijentisanim poslovnim sistemima. Dva problema u značajnoj meri utiču na usvajanje adaptabilnih procesno- orijentisanih poslovnih sistema. Prvi problem se odnosi na kompleksnost ove aktivnosti. Izmena modela procesa i kreiranje nove verzije koja će se koristiti za buduće instance je postupak koji je uobičajen, dobro poznat i u širokoj upotrebi. Ali adaptacija koja se propagira trenutno i na već pokrenute instance procesa nosi mnogo više nepoznanica i potencijalnih problema. Neophodno je sagledati trenutno stanje izvršavanja svake pojedine instance, izvršiti evaluaciju primenjivosti u kontekstu svake od tih instanci. Potrebno znanje za primenjivanje ovakvog pristupa, odnosno kreiranje rešenja sa podrškom za adaptabilnost procesa podrazumeva i mogućnost analitičkog sagledavanja posledica koje takva izmena može imati na procesne instance koje se već izvršavaju. Neophodno je dosta iskustva kako bi se sa sigurnošću predvidelo da li implementacija neke nove promene u već pokrenutoj instanci ne dovodi u pitanje samo izvršavanje procesa. Procesna okruženja koja podržavaju adaptabilnost bi stoga trebala da pruže alat koji omogućava da se ove provere sprovedu pre nego što do neželjenih posledica dođe. Drugi problem nastaje zbog nedostatka postojanja konkretne paradigme koja bi opisala način primene ove aktivnosti, odnosno slučajevi koji zahtevaju primenu adaptabilnosti se razlikuju i specifični su u zavisnosti od ciljanog poslovnog sistema. Cilj ove disertacije, na osnovu pomenutog, je kreiranje tehničkog rešenja koje će pružati podršku za adaptabilnost procesa u procesno- orijentisanim poslovnim sistemima, kao i odgovor na pitanje, kako i u kojoj meri je moguće primeniti adaptabilnost na tekućim procesima u procesno orijentisanim poslovnim sistemima.Research topic of this dissertation is from the area of software engineering and business processes and business process management. An ever-increasing demand for information systems in the last few decades brought many new opportunities but also presented new challenges for companies in the landscape of doing business globally. In these terms, software systems need to adapt almost instantaneously to new requirements, opportunities, and customer expectations. Process-aware systems have become integral part in business information system solutions, finding their place at different locations. Process and data models, as well as tools on which process-oriented information systems are based, have the task of ensuring controlled management and predictable execution of business processes. The basic premise for the functioning of such systems is that the business function can be represented as a process and/or workflow - an orchestrated chain of activities (tasks), which when performed in a defined sequence, give a successful process outcome. Adapting to changes in a business process has become one of the most important activities in modern business information systems. However, the effective application of this activity in the context of modern business assessment-oriented systems is somewhat limited by the implementation methods of the process systems themselves, which usually make a strict distinction between process models and instances created on the basis of such models. Two problems significantly affect the adoption of adaptable process-oriented business systems. The first problem is related to the complexity of this activity. Modifying a process model and creating a new version to be used for future instances is a procedure that is common, well-known, and widely used. But the adaptation that propagates currently and to already started instances of the process carries many more unknowns and potential problems. It is necessary to look at the current state of execution of each individual instance, to evaluate the applicability in the context of each of those instances. A lot of experience is necessary in order to predict with certainty whether the implementation of a new change in an already started instance does not call into question the execution of the process itself. Process environments that support adaptability should therefore provide tools that enable these checks to be carried out before unintended consequences occur. Another problem arises due to the lack of existence of a concrete paradigm that would describe the way of applying this activity, that is, the cases that require the application of adaptability differ and are specific depending on the targeted business system. The goal of this dissertation, based on the aforementioned, is to create a technical solution that will provide support for process adaptability in processoriented business systems, as well as an answer to the question of how and to what extent it is possible to apply adaptability to ongoing processes in process-oriented business systems

    A Survey on Process Variants Meta-modelling Approaches

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    This paper introduces the concept of process variants in process-aware information systems (PAIS) during the design-time phase, where multiple variants of a single process must be specified. Today's organizations have to manage multiple variants of a given process, such as multiple order processes or payment processes for a specific product or service they offer. Traditional business process management tools lack in adequately capture and represent explicitly these variants. Hence, for more than a decade an array of approaches have been proposed to tackle this gap. A reference or customizable process model has been introduced to model these variants collections in a way that each variant could be derived by inserting/removing an activity according to a process context. This survey reviews current literature by providing an overview of meta-modelling approaches that have been extended in order to capture the variations of business processes. Moreover, we give a comparative analysis of these approaches based on different criteria we identified from the inventory activity, providing insights into their strengths and limitations. This paper concludes that current approaches to process variants meta-modelling provide a comprehensive view of the conceptual level of process variants and the control-flow process perspective. While some approaches go a step further by capturing variability in resources or specialization among activities/processes

    Improving data preparation for the application of process mining

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    Immersed in what is already known as the fourth industrial revolution, automation and data exchange are taking on a particularly relevant role in complex environments, such as industrial manufacturing environments or logistics. This digitisation and transition to the Industry 4.0 paradigm is causing experts to start analysing business processes from other perspectives. Consequently, where management and business intelligence used to dominate, process mining appears as a link, trying to build a bridge between both disciplines to unite and improve them. This new perspective on process analysis helps to improve strategic decision making and competitive capabilities. Process mining brings together data and process perspectives in a single discipline that covers the entire spectrum of process management. Through process mining, and based on observations of their actual operations, organisations can understand the state of their operations, detect deviations, and improve their performance based on what they observe. In this way, process mining is an ally, occupying a large part of current academic and industrial research. However, although this discipline is receiving more and more attention, it presents severe application problems when it is implemented in real environments. The variety of input data in terms of form, content, semantics, and levels of abstraction makes the execution of process mining tasks in industry an iterative, tedious, and manual process, requiring multidisciplinary experts with extensive knowledge of the domain, process management, and data processing. Currently, although there are numerous academic proposals, there are no industrial solutions capable of automating these tasks. For this reason, in this thesis by compendium we address the problem of improving business processes in complex environments thanks to the study of the state-of-the-art and a set of proposals that improve relevant aspects in the life cycle of processes, from the creation of logs, log preparation, process quality assessment, and improvement of business processes. Firstly, for this thesis, a systematic study of the literature was carried out in order to gain an in-depth knowledge of the state-of-the-art in this field, as well as the different challenges faced by this discipline. This in-depth analysis has allowed us to detect a number of challenges that have not been addressed or received insufficient attention, of which three have been selected and presented as the objectives of this thesis. The first challenge is related to the assessment of the quality of input data, known as event logs, since the requeriment of the application of techniques for improving the event log must be based on the level of quality of the initial data, which is why this thesis presents a methodology and a set of metrics that support the expert in selecting which technique to apply to the data according to the quality estimation at each moment, another challenge obtained as a result of our analysis of the literature. Likewise, the use of a set of metrics to evaluate the quality of the resulting process models is also proposed, with the aim of assessing whether improvement in the quality of the input data has a direct impact on the final results. The second challenge identified is the need to improve the input data used in the analysis of business processes. As in any data-driven discipline, the quality of the results strongly depends on the quality of the input data, so the second challenge to be addressed is the improvement of the preparation of event logs. The contribution in this area is the application of natural language processing techniques to relabel activities from textual descriptions of process activities, as well as the application of clustering techniques to help simplify the results, generating more understandable models from a human point of view. Finally, the third challenge detected is related to the process optimisation, so we contribute with an approach for the optimisation of resources associated with business processes, which, through the inclusion of decision-making in the creation of flexible processes, enables significant cost reductions. Furthermore, all the proposals made in this thesis are validated and designed in collaboration with experts from different fields of industry and have been evaluated through real case studies in public and private projects in collaboration with the aeronautical industry and the logistics sector

    A Deep Learning Approach to Business Process Mining

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    Competing and evolving markets force organisations to continuously monitor, evaluate, and optimise their business processes. To do the task at scale, organisations often turn to automatic mining of process execution logs constantly generated by various information systems. Many open-source and commercial tools have been developed in recent years to help organisations perform various process mining tasks using process execution logs (often called event logs), such as process discovery, conformance checking, and detecting drifts in processes. Compared to traditional process mining techniques such as Petri nets and Business Process Model and Notation (BPMN), deep learning methods such as Recurrent Neural Networks and Long Short-Term Memory (LSTM) in particular have proven to achieve better performance in terms of accuracy and generalising ability when predicting sequences of activities performed as part of business processes based on event logs. However, unlike traditional network-based process mining techniques that can be used to visually present all activity sequences of the discovered business process, existing deep learning-based methods for process mining lack a mechanism explaining how the activity sequence predictions are made. To address this limitation, this thesis proposes an extensible process mining solution that combines the benefits of interpretable graph-based methods and more accurate but implicit deep learning methods. The main contributions of this research are: (i) building an LSTM model for predicting business process activity sequences from event logs that outperforms existing state-of-the-art deep learning solutions; (ii) proposing a graph-based approach to explaining the decision-making process of the LSTM model when predicting business process activity sequences; and (iii) developing methods for detecting and localising sudden concept drift in event logs (i.e., offline) and event streams (i.e., online) using deep learning and graph-based approaches. The proposed methods have been extensively evaluated by conducting experiments using real-life and artificial event logs and have been demonstrated to outperform existing state-of-the-art solutions in many cases

    Vérification efficace de systèmes à compteurs à l'aide de relaxations

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    Abstract : Counter systems are popular models used to reason about systems in various fields such as the analysis of concurrent or distributed programs and the discovery and verification of business processes. We study well-established problems on various classes of counter systems. This thesis focusses on three particular systems, namely Petri nets, which are a type of model for discrete systems with concurrent and sequential events, workflow nets, which form a subclass of Petri nets that is suited for modelling and reasoning about business processes, and continuous one-counter automata, a novel model that combines continuous semantics with one-counter automata. For Petri nets, we focus on reachability and coverability properties. We utilize directed search algorithms, using relaxations of Petri nets as heuristics, to obtain novel semi-decision algorithms for reachability and coverability, and positively evaluate a prototype implementation. For workflow nets, we focus on the problem of soundness, a well-established correctness notion for such nets. We precisely characterize the previously widely-open complexity of three variants of soundness. Based on our insights, we develop techniques to verify soundness in practice, based on reachability relaxation of Petri nets. Lastly, we introduce the novel model of continuous one-counter automata. This model is a natural variant of one-counter automata, which allows reasoning in a hybrid manner combining continuous and discrete elements. We characterize the exact complexity of the reachability problem in several variants of the model.Les systèmes à compteurs sont des modèles utilisés afin de raisonner sur les systèmes de divers domaines tels l’analyse de programmes concurrents ou distribués, et la découverte et la vérification de systèmes d’affaires. Nous étudions des problèmes bien établis de différentes classes de systèmes à compteurs. Cette thèse se penche sur trois systèmes particuliers : les réseaux de Petri, qui sont un type de modèle pour les systèmes discrets à événements concurrents et séquentiels ; les « réseaux de processus », qui forment une sous-classe des réseaux de Petri adaptée à la modélisation et au raisonnement des processus d’affaires ; les automates continus à un compteur, un nouveau modèle qui combine une sémantique continue à celles des automates à un compteur. Pour les réseaux de Petri, nous nous concentrons sur les propriétés d’accessibilité et de couverture. Nous utilisons des algorithmes de parcours de graphes, avec des relaxations de réseaux de Petri comme heuristiques, afin d’obtenir de nouveaux algorithmes de semi-décision pour l’accessibilité et la couverture, et nous évaluons positivement un prototype. Pour les «réseaux de processus», nous nous concentrons sur le problème de validité, une notion de correction bien établie pour ces réseaux. Nous caractérisions précisément la complexité calculatoire jusqu’ici largement ouverte de trois variantes du problème de validité. En nous basant sur nos résultats, nous développons des techniques pour vérifier la validité en pratique, à l’aide de relaxations d’accessibilité dans les réseaux de Petri. Enfin, nous introduisons le nouveau modèle d’automates continus à un compteur. Ce modèle est une variante naturelle des automates à un compteur, qui permet de raisonner de manière hybride en combinant des éléments continus et discrets. Nous caractérisons la complexité exacte du problème d’accessibilité dans plusieurs variantes du modèle
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