An Approach to Business Process Reengineering Based on the Integration of Methods of Processes Mining and Domain Specific Modelling Abstract: An approach to business process reengineering on the basis of integration of DSM platform and Process Mining tools is offered. Implementation of the integrated tools allows to reduce laboriousness of analysts work, to provide close rapport between specialists.
Prediction of the duration of a repair and maintenance project of a gas transport system is an important part of planning activities. There exist numerous sources of uncertainties that may result in time overruns possibly leading to multiple negative consequences. Our experience in planning this work suggests that accepting the stochastic nature of the project duration is a constructive step towards the preparedness to contingencies and defining penalties for repair companies. To support this approach, one needs to construct probability distributions of the durations of the projects. To address the issue of the scarcity of observed data, we suggest using a bootstrap resampling procedure. Gram-Charlier functions and order statistics are employed to approximate the distributions. It is demonstrated how to derive them for a separate repair project and a larger project consisting of a number of concurrently running subprojects. Following this, guidance is provided on how to decide about what duration should define the deadline for completion of the whole work. A simple example is provided.
Monitoring and analyzing the operation of enterprises is a key capability of Governance, Risk, and Compliance (GRC) solutions and is relevant for high-risk organizations, such as financial services. The potential of state-of-the-art process mining (data-driven process analysis) is limited by quality issues with transactional data registration and extraction. A novel approach is proposed to address these challenges: the Enterprise Operational Analysis (EOA) founded in DEMO and the Enterprise Operating System (EOS). The EOS is a software system based on enterprise engineering, and stores, interprets, and executes DEMO models as native source code. The EOS provides workflow-like capabilities and supports EOA. Combining the EOS with state-of-the-art process mining offers the following advantages: guaranteed completeness of analysis, elimination of ‘mining’ for events, facilitating process conformance checking, analysis on various levels of granularity from various perspectives. It enables enterprises to systematically analyze, improve and deploy business procedures. A professional business case is analyzed. © Springer International Publishing Switzerland 2015.
Comparing business process models is one of the most significant challenges for business and systems analysts. The complexity of the problem is explained by the fact there is a lack of tools that can be used for comparing business process models. Also there is no universally accepted standard for modeling them. EPC, YAWL, BPEL, XPDL and BPMN are only a small fraction of available notations that have found acceptance among developers. Every process modeling standard has its advantages and disadvantages, but almost all of them comprise an XML schema, which defines process serialization rules. Due to the fact that XML naturally represents hierarchical and reference structure of business process models, these models can be compared using their XML representations. In this paper we propose a generic comparison approach, which is applicable to XML representations of business process models. Using this approach we have developed a tool, which currently supports BPMN 2.0 (one of the most popular business process modeling notations), but can be extended to support other business process modeling standards. This paper is an ongoing research conducted in the frame of a bachelor diploma in the software engineering field.
Process mining is a relatively new field of computer science, which deals with process discovery and analysis based on event logs. In this paper we consider the problem of models and event logs conformance checking. Conformance checking is intensively studied in the frame of process mining research, but only models and event logs of the same granularity were considered in the literature. Here we present and justify the method of checking conformance between a high-level model (e.g. built by an expert) and a low-level log (generated by a system).
The issue contains papers accepted for presentation at the 10th Spring/Summer Young Researchers’ Colloquium on Software Engineering (SYRCoSE 2016) held in Krasnovidovo, Mozhaysky District, Moscow Oblast, Russia on May 30-June 1, 2016. The paper selection was based on originality and contributions to the field. Each paper was peer-reviewed by at least three referees.
The colloquium’s topics include programming languages, software development tools, embedded and cyber-physical systems, software and hardware verification, formal methods, information security, and others.