Published January 24, 2023 | Version 1.0
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Problem discovery and resolution activities in the Apache HTTP Server Project (March 2001- March 2013).

  • 1. University of Greenwich, London (UK)
  • 2. University of Konstanz (Germany)
  • 3. University of Italian Switzerland, Lugano (Switzerland)
  • 4. University of Exeter (UK)
  • 5. University of Trento (Italy)
  • 1. Università degli Studi di Trento
  • 2. University of Exeter
  • 3. University of Greenwich
  • 4. Uiversity of Konstanz
  • 5. Università della Svizzera italiana

Description

This is a dynamic visualization of problem discovery and resolution activities observed in the in the development of the Apache HTTP Server Project during the period March 2001- March 2013. The nodes in the network represent problems (software bugs). Anthropomorphic icons represent participants (software developers). The network edges connect participants to problems.  Numerical labels record the internal identification numbers or participants and problems.  The visible clusters represent the software modules. The central node is the project core module. Participants move closer to problems that attract their attention. When a participant allocates attention to a problem, an edge emerges connecting the two. The edge is green when a participant opens a bug report (i.e., when he discovers a new problem), red when the participant closes the bug report (i.e., when she solves an existing problem), and yellow when any other action is recorded. Problems (white nodes) are green when they first appear. They turn red immediately before being closed, and are yellow when the corresponding bug report is being modified.  The animation advances by 0.05 seconds every day of historical time.

The animation is produced using the Gource server control visualization tool developed by Andrew Caldwell (https://gource.io/)

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Apache-HTTP-white.mp4

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Additional details

Related works

Is cited by
Peer review: 10.1287/orsc.2023.1674 (DOI)

Funding

Swiss National Science Foundation
Relational event models for bipartite networks with applications to collaborative problem solving in organizations 100018_150126

References

  • Tonellato, M., Tasselli, S., Conaldi, G., Lerner, J., & Lomi, A. (2023). A microstructural approach to self-organizing: The emergence of attention networks.