Mining for User-Defined Categorizations as an Approach for Process Simplification in Business Process Discovery

Business process discovery approaches analyse event logs to create process models describing the as-is state of the underlying processes. Because this type of process mining is especially relevant for low structured processes, there are approaches designed to deal with such processes by simplifying the resulting model. Such simplifications are primarily applied with metrics based on the frequency of observed behaviour. However, a high frequency of certain behaviour is not synonymous with a high relevance to the user. Consequently, this paper applies a design science research approach to design and implement a business process discovery approach based on user-defined categories to guarantee relevance to the respective user. During one design science research cycle, a design theory consisting of design requirements and design principles is constructed, a method called categorization approach is created, and this method implemented in a software artefact is evaluated with regard to perceived usefulness in an expert survey

Methods and Tool for Process Validation

Cieľom diplomovej práce je porozumieť oblasti process miningu a postupne prejsť všetkými definovanými úrovňami tejto problematiky – porozumenie, aplikácia, výskum, vývoj. Výsledkom práce bude návrh a vytvorenie novej metodiky verifikácie procesných modelov, ktorá bude implementovaná ako rozšírenie v nástroji ProM.The objective of the Master Thesis is to understand the domain of the process mining and gradually passing through all defined levels of this issue – understanding, application, research, development. The result will be the design and implementation of a new methodology for process model verification, which will be implemented as an extension in the ProM tool.460 - Katedra informatikydobř

Process Mining as a Service

Softwérové a hardvérové aplikácie zaznamenávajú veľké množstvo informácií do protokolov udalostí. Každé dva roky sa množstvo zaznamenaných dát viac než zdvojnásobí. Dolovanie procesov je relatívne mladá disciplína, ktorá sa nachádza na rozmedzí strojového učenia a dolovania dát na jednej strane a modelovania a analýzy procesov na druhej strane. Cieľom dolovania procesov je popísať a analyzovať skutočné procesy extrahovaním znalostí z protokolov udalostí, ktoré sú v dnešných aplikáciách bežne dostupné. Táto práca mieri na spojenie obchodných príležitostí (organizácie bohaté na dáta; dopyt po službách BPM; limitácie na strane tradičnej dodávky BPM služieb) s technickými možnosťammi Dolovania procesov. Cieľom práce je návrh produktu, ktorý bude riešiť potreby zákazníkov a poskytovateľov služieb v oblasti Dolovania procesov lepšie než súčasné riešenie vybranej spoločnosti.The software and hardware applications record more and more information into the event logs. The amount of data recorded is more than doubled every two years. Process mining is a relatively young discipline that sits between machine learning and data mining on the one hand and process modeling and analysis on the other hand. The goal of process mining is to describe and analyze real processes by extracting knowledge from the event logs readily available in today’s systems. This thesis aims to connect the business opportunities (i.e., data-rich organizations; need for BPM services; limitation in traditional delivery of BPM services) with technical possibilities of Process mining. The goal is to propose a product solving needs and demands of stakeholders (i.e., customers and consultants) better than select existing solution.

Prosessilouhintamallin luominen normaalimuutosprosessin tueksi

Liiketoimintaympäristö muuttuu ja yritykset pyrkivät pysymään muutosten mukana kehittämällä liiketoimintaprosesseja. Tietojärjestelmät tuottavat paljon tietoa, jonka hyödyntäminen on vielä vähäistä. Prosessilouhinta mahdollistaa tietojärjestelmien tuottaman tiedon käyttämisen liiketoimintaprosessien kehittämisessä. Tämä tutkimus on syntynyt kohdeyrityksen tarpeesta saada lisää läpinäkyvyyttä ja parantaa tiedolla johtamista IT-palvelunhallintaan kuuluvan muutoksenhallinnan normaalimuutosprosessissa. Tutkimus seuraa suunnittelututkimusprosessin viitekehystä. Tutkimuksen tavoitteena oli selvittää prosessilouhinnan edellytykset ja mahdollisuudet normaalimuutosprosessin tueksi. Tutkimuksessa suunniteltiin, luotiin ja arvioitiin artefakti, joka tässä tapauksessa oli prosessilouhintamalli. Prosessilouhintamallin tavoitteena oli lisätä tutkittavan prosessin läpinäkyvyyttä ja kehittää tiedolla johtamista. Prosessilouhintamallin suunnittelussa oli keskeistä tunnistaa lähdejärjestelmästä tarvittavat tiedot ja luoda tietoihin pohjautuva tapahtumaloki. Tapahtumaloki oli edellytys prosessilouhinnan suorittamiselle. Tutkimuksessa käytettiin lähdejärjestelmän kehittäjäympäristöstä saatuja tietoja, koska tuotantoympäristöön ei saatu tarvittavia käyttöoikeuksia tutkimuksen aikarajojen puitteissa. Kehittäjäympäristön tiedot olivat heikkolaatuisia, jotka aiheuttivat artefaktin arvioinnissa haasteita. Prosessilouhintamallin arviointi tapahtui haastattelemalla kohdeyrityksen muutoksenhallintaprosessin avainhenkilöitä. Tutkimuksen tuloksena onnistuttiin luomaan prosessilouhintamalli sekä yleisesti syventämään kohdeyrityksen ymmärrystä ja osaamista prosessilouhinnasta. Luotu prosessilouhintamalli lisäsi prosessin läpinäkyvyyttä esittämällä prosessin aikaiset tapahtumat. Tapauksia pystytään tarkastelemaan kokonaisuutena ja yksittäisinä. Päätöksenteon taustalla on enemmän tietoa, kun prosessilouhintamallia käytetään. Näin ollen tiedolla johtaminen kehittyy ja kohdeyritys pystyy tunnistamaan ongelmakohdat tarkemmin, joihin resurssit voidaan kohdentaa tehokkaasti. Tutkimuksen avulla pystyttiin myös kasvattamaan kohdeyrityksen ymmärrystä teknologian mahdollisuuksista. Prosessilouhinnan laajempi käyttöönotto koettiin mahdolliseksi kohdeyrityksessä. Haasteiksi koettiin lisäresurssien tarve ja muutoksen merkittävyys. Prosessilouhinnan käyttöönotto vie aikaa ja vaatii sitoutumista koko yritykseltä. Tutkimusprosessia seuraten kohdeyritys voi tarkastella muitakin prosesseja. Tutkimuksesta on hyötyä myös muille yrityksille, jotka ovat kiinnostuneita, miten toteuttaa yksi tunnistettu käyt-tötapaus. Seuraavana askeleena kohdeyritykselle on käyttää tuotantoympäristön tietoja, joiden avulla kehittää luotua prosessilouhintamallia ja analysoimalla prosessia syvällisesti. Lisäksi kohdeyritys voi alkaa laajentamaan käyttöönottoa muihin prosesseihin.Business environment is changing, and companies try to keep up with change by developing business processes. Information systems produce lots of information which is not greatly utilised. Process mining enables the usage of data produced by systems in business process development. This research has originated from the target company’s needs to increase transparency and enhance knowledge management in change management’s normal change process. The research utilises design science research framework. The objective of the research was to investigate requirements and opportunities of process mining to support normal change process. In the research an artefact was designed, created, and evaluated which was a process mining model in this case. The objective of the process mining model was to increase transparency of the process and develop knowledge management. The essential part of designing process mining model was to identify required data from the source system and create an event log based on the data. Event log was required to perform process mining. Data from source system’s development environment was used in the research because access rights to production environment was not granted during the research timeframe. Development environment data was low quality which caused challenges during artefact’s evaluation phase. Evaluating the process mining model was conducted by interviewing target company’s key personnel in change management process. As a result of the research process mining model was successfully created and overall target company’s process mining knowledge was enhanced. The created process mining model increased transparency of the process by illustrating the activities during the process. Cases can be examined as a group and individually. There is more information available to support decision making. Therefore, knowledge management is evolving, and target company can efficiently identify problems where resources can be allocated. Target company was also able to gain more understanding about the opportunities of the technology. Extensive implementation of process mining was considered possible in target company. Perceived challenges to implementation are need for additional resources and magnitude of the change. Implementing process mining takes time and requires commitment from the whole company. By using the conducted research process target company can examine other processes as well. The research is useful for other companies which are interested to learn how specific use case was implemented. Next step for the target company is to use data from production environment to develop the created process mining model and analyse the process profoundly. In addition, implementation of process mining can be extended to other processes

ICSEA 2022: the seventeenth international conference on software engineering advances

The Seventeenth International Conference on Software Engineering Advances (ICSEA 2022), held between October 16th and October 20th, 2022, continued a series of events covering a broad spectrum of software-related topics. The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. Several tracks were proposed to treat the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learned. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education. Other advanced aspects are related to on-time practical aspects, such as run-time vulnerability checking, rejuvenation process, updates partial or temporary feature deprecation, software deployment and configuration, and on-line software updates. These aspects trigger implications related to patenting, licensing, engineering education, new ways for software adoption and improvement, and ultimately, to software knowledge management. There are many advanced applications requiring robust, safe, and secure software: disaster recovery applications, vehicular systems, biomedical-related software, biometrics related software, mission critical software, E-health related software, crisis-situation software. These applications require appropriate software engineering techniques, metrics and formalisms, such as, software reuse, appropriate software quality metrics, composition and integration, consistency checking, model checking, provers and reasoning. The nature of research in software varies slightly with the specific discipline researchers work in, yet there is much common ground and room for a sharing of best practice, frameworks, tools, languages and methodologies. Despite the number of experts we have available, little work is done at the meta level, that is examining how we go about our research, and how this process can be improved. There are questions related to the choice of programming language, IDEs and documentation styles and standard. Reuse can be of great benefit to research projects yet reuse of prior research projects introduces special problems that need to be mitigated. The research environment is a mix of creativity and systematic approach which leads to a creative tension that needs to be managed or at least monitored. Much of the coding in any university is undertaken by research students or young researchers. Issues of skills training, development and quality control can have significant effects on an entire department. In an industrial research setting, the environment is not quite that of industry as a whole, nor does it follow the pattern set by the university. The unique approaches and issues of industrial research may hold lessons for researchers in other domains. We take here the opportunity to warmly thank all the members of the ICSEA 2022 technical program committee, as well as all the reviewers. The creation of such a high-quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and effort to contribute to ICSEA 2022. We truly believe that, thanks to all these efforts, the final conference program consisted of top-quality contributions. We also thank the members of the ICSEA 2022 organizing committee for their help in handling the logistics of this event. We hope that ICSEA 2022 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in software engineering advances