Process anti-pattern detection – a case study

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43967863" target="_blank" >RIV/49777513:23520/22:43967863 - isvavai.cz</a>

Result on the web

<a href="https://dl.acm.org/doi/10.1145/3551902.3551965" target="_blank" >https://dl.acm.org/doi/10.1145/3551902.3551965</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3551902.3551965" target="_blank" >10.1145/3551902.3551965</a>

Result language

angličtina

Original language name

Process anti-pattern detection – a case study

Original language description

Anti-patterns are harmful phenomena repeatedly occurring, e.g., in software development projects. Though widely recognized and well-known, their descriptions are traditionally not fit for automated detection. The detection is usually performed by manual audits, or on business process models. Both options are time-, effort- and expertise-heavy, prone to biases, and/or omissions. Meanwhile, collaborative software projects produce much data as a natural side product, capturing their status and day-to-day history. Long-term, our research aims at deriving models for the automated detection of process and project management anti-patterns, applicable to project data. Here, we present a general approach for studies investigating occurrences of these types of anti-patterns in projects and discuss the entire process of such studies in detail, startingfrom the anti-pattern descriptions in literature. We demonstrate and verify our approach with the Fire Drill anti-pattern detection as a case study, applying it to data from 15 student projects. The results of our study suggest that reliable detection of at least some process and project management anti-patterns in project data is possible, with 13 projects assessed accurately for Fire Drill presence by our automated detection when compared to the ground truth gathered from independent data. The overall approach can be similarly applied to detecting patterns and other phenomena with manifestations in Application Lifecycle Management data.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EF17_048%2F0007267" target="_blank" >EF17_048/0007267: Research and Development of Intelligent Components of Advanced Technologies for the Pilsen Metropolitan Area (InteCom)</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 27th European Conference on Pattern Languages of Programs 2022

ISBN

978-1-4503-9594-6

ISSN

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e-ISSN

—

Number of pages

18

Pages from-to

1-18

Publisher name

The Association for Computing Machinery

Place of publication

1601 Broadway, New York, New York 10019, USA

Event location

Irsee, Německo

Event date

Jul 6, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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