SEFeb 25, 2017

Revealing Task Driven Knowledge Worker Behaviors in Open Source Software Communities

arXiv:1702.07900v1Has Code
Originality Synthesis-oriented
AI Analysis

This provides insights into human dynamics for researchers studying online collaboration, but it is incremental as it supplements existing work without introducing new methods.

The paper tackled the problem of understanding behavioral patterns of software developers in open-source communities by analyzing bug tracking data from Eclipse and Mozilla, finding that developers exhibit opposite patterns under normal vs. overload states and that processing times follow a stretched exponential distribution.

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) follow a stretched exponential distribution instead of the common power law distribution. Our work reveals regular patterns in human dynamics beyond online collaborative activities among skilled developers who work under different task-driven load conditions, and it could be an important supplementary to the current work on human dynamics.

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