On the Difficulty of Identifying Incident-Inducing Changes

Eileen Kapel*, Luis Cruz, Diomidis Spinellis, Arie Van Deursen

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Effective change management is crucial for businesses heavily reliant on software and services to minimise incidents induced by changes. Unfortunately, in practice it is often difficult to effectively use artificial intelligence for IT Operations (AIOps) to enhance service management, primarily due to inadequate data quality. Establishing reliable links between changes and the induced incidents is crucial for identifying patterns, improving change deployment, identifying high-risk changes, and enhancing incident response. In this research, we investigate the enhancement of traceability between changes and incidents through AIOps methods. Our approach involves a close examination of incident-inducing changes, the replication of methods linking incidents to the changes that caused them, introducing an adapted method, and demonstrating its results using historical data and practical evaluations. Our findings reveal that incident-inducing changes exhibit different characteristics dependent on context. Furthermore, a significant disparity exists between assessments based on historical data and real-world observation, with an increased occurrence of false positives when identifying links between unlabeled changes and incidents. This study highlights the complex nature of identifying links between changes and incidents, emphasising the contextual influence on AIOps method effectiveness. While we are actively working on improving the quality of current data through AIOps approaches, it remains apparent that further measures are necessary to address issues like data imbalances and promote a postmortem culture that brings attention to the value of properly administrating tickets. A better overview of change failure rates contributes to improved risk compliance and reliable change management.

Original languageEnglish
Title of host publicationProceedings - 2024 ACM/IEEE 44th International Conference on Software Engineering
Subtitle of host publicationNew Ideas and Emerging Results, ICSE-SEIP 2024
PublisherAssociation for Computing Machinery (ACM)
Pages36-46
Number of pages11
ISBN (Electronic)9798400705007
DOIs
Publication statusPublished - 2024
Event2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results, ICSE-SEIP 2024 - Lisbon, Portugal
Duration: 14 Apr 202420 Apr 2024

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results, ICSE-SEIP 2024
Country/TerritoryPortugal
CityLisbon
Period14/04/2420/04/24

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • change management
  • incident management
  • traceability

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