Activity-Based Detection of (Anti-)Patterns: An Embedded Case Study of the Fire Drill

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43971999" target="_blank" >RIV/49777513:23520/24:43971999 - isvavai.cz</a>

Result on the web

<a href="https://www.e-informatyka.pl/index.php/einformatica/volumes/volume-2024/issue-1/article-6/" target="_blank" >https://www.e-informatyka.pl/index.php/einformatica/volumes/volume-2024/issue-1/article-6/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.37190/e-Inf240106" target="_blank" >10.37190/e-Inf240106</a>

Result language

angličtina

Original language name

Activity-Based Detection of (Anti-)Patterns: An Embedded Case Study of the Fire Drill

Original language description

Background: Nowadays, expensive, error-prone, expert-based evaluations are needed to identify and assess software process anti-patterns. Process artifacts cannot be automatically used to quantitatively analyze and train prediction models without exact ground truth. Aim: Develop a replicable methodology for organizational learning from process (anti-)patterns, demonstrating the mining of reliable ground truth and exploitation of process artifacts. Method: We conduct an embedded case study to find manifestations of the Fire Drill anti-pattern in n = 15 projects. To ensure quality, three human experts agree. Their evaluation and the process’ artifacts are utilized to establish a quantitative understanding and train a prediction model. Results: Qualitative review shows many project issues. (i) Expert assessments consistently provide credible ground truth. (ii) Fire Drill phenomenological descriptions match project activity time (for example, development). (iii) Regression models trained on ≈ 12–25 examples are sufficiently stable. Conclusion: The approach is data source-independent (source code or issue-tracking). It allows leveraging process artifacts for establishing additional phenomenon knowledge and training robust predictive models. The results indicate the aptness of the methodology for the identification of the Fire Drill and similar anti-pattern instances modeled using activities. Such identification could be used in post mortem process analysis supporting organizational learning for improving processes.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

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

2024

Confidentiality

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

Name of the periodical

e-Informatica Software Engineering Journal (EISEJ)

ISSN

1897-7979

e-ISSN

2084-4840

Volume of the periodical

18

Issue of the periodical within the volume

1

Country of publishing house

PL - POLAND

Number of pages

49

Pages from-to

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UT code for WoS article

001229559900001

EID of the result in the Scopus database

2-s2.0-85188276370