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Adrian Cryer

dblp:362/4414 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0007-7887-0603ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data mining · 77% Data stream processing · 23%
Software engineering, system software, and programming languages
1 paper
Services computing and microservices · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data mining › process mining
event log analysis
0.712023
Cross-Instance Regulatory Compliance Checking of Business Process Event Logs · IEEE Trans. Software Eng. 2023
Services computing and microservices › business process management
business process compliance checking
0.712023
Cross-Instance Regulatory Compliance Checking of Business Process Event Logs · IEEE Trans. Software Eng. 2023

Methods — techniques the papers use, named apart from their topics

sequence attribute function evaluation · 1.3
YearPublicationVenuePosition
2023 Cross-Instance Regulatory Compliance Checking of Business Process Event Logs
abstract
Event logs capture the execution of business processes, such that each task is represented by an event and each individual execution is a chronological sequence of events, called an event trace. Event logs allow after-the-act and runtime analysis of deployed business processes to verify whether their execution complies with regulations and business requirements. Checking the compliance of a single sequence of events in a trace is straightforward and a number of approaches have been proposed to address this. However, some regulations or business rules span multiple process instances, requiring a cross-instance analysis. In order to check whether such requirements are maintained at all times, multiple traces need to be analysed together, which can result in a combinatorial computational complexity. In this article, we present a novel approach that efficiently checks runtime regulatory compliance based on event logs, while supporting cross-instance rule evaluation and extensible function evaluation over sequences of attribute data values. The efficiency and applicability of the proposed method is tested in a two-pronged evaluation, showing a significant improvement over existing techniques with respect to capabilities as well as computational complexity. The approach presented in this paper is subject to a patent application, with patent number WO2021/248201.
Nick R. T. P. van Beest, Heerko Groefsema, Adrian Cryer, Guido Governatori, Silvano Colombo Tosatto, Hannah M. S. Burke
IEEE Trans. Software Eng.3