logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

Bottleneck Analysis in Software Development: A Case Study Using Process Mining

delete2026-01-01
delete0
PRE
AI
R
Rodrigo Almeida de Oliveira *
J
Juliano de Paulo Ribeiro
E
Edson Emílio Scalabrin
DOI：10.1007/978-3-032-03708-4_22delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Bottleneck analysis in software development highlights inefficiencies that hinder team productivity. This study uses Process Mining techniques to identify and address bottlenecks in workflows by analyzing event logs from IDEs and task management systems. The approach involves process discovery, conformance checking, and predictive modeling to detect inefficiencies and deviations. A predictive model was developed to anticipate future bottlenecks, allowing for targeted interventions. Major bottlenecks included delays in communication, redundant task cycles, and misallocated resources. Workflow adjustments, such as process redesign and task redistribution, led to a 38% improvement in efficiency overall like reduction of queue time. The study highlights the role of Process Mining in optimizing development workflows, with a focus on data quality and system integration for accurate analysis.
Keywords:
Process Mining
Bottleneck Analysis
Workflow Optimization
Process Efficiency

Journal

A
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2025, PT II
IF:
0
Papers:
30
Citations:
0

Organization

No organization information available