Revealing Task Driven Knowledge Worker Behaviors in Open Source Software Communities
Hongrui Wu, Xiaowan Shi, Yutao Ma

TL;DR
This study analyzes behavioral patterns of software developers in open source communities, revealing distinct behaviors under different workload states and showing that processing times follow a stretched exponential distribution, contributing to understanding human dynamics in online collaboration.
Contribution
It provides the first empirical analysis of developer behaviors under varying load conditions in OSS communities, highlighting distinct patterns and distribution types of processing times.
Findings
Developers show opposite behavioral patterns under normal and overload states.
Bug fixing and tossing times follow a stretched exponential distribution.
Behavioral patterns reveal regularities in human dynamics in online collaborative work.
Abstract
Collaborative activities among knowledge workers such as software developers underlie the development of modern society, but the in-depth understanding of their behavioral patterns in open online communities is very challenging. The availability of large volumes of data in open-source software (OSS) repositories (e.g. bug tracking data, emails, and comments) enables us to investigate this issue in a quantitative way. In this paper, we conduct an empirical analysis of online collaborative activities closely related to assure software quality in two well-known OSS communities, namely Eclipse and Mozilla. Our main findings include two aspects: (1) developers exhibit two diametrically opposite behavioral patterns in spatial and temporal scale when they work under two different states (i.e. normal and overload), and (2) the processing times (including bug fixing times and bug tossing times)…
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Taxonomy
TopicsOpen Source Software Innovations · Software Engineering Research · Mobile Crowdsensing and Crowdsourcing
