analyzing routine structures in open source software development digital traces & qualitative...
TRANSCRIPT
Analyzing Routine Structures in Open Source Software Development Digital Traces & Qualitative Inquiry
Aron LindbergCase Western Reserve University
Research Problems
• How do OSS projects match the complexity of problems with requisite complexity of routines?
• How do OSS projects differ in terms of their performative, routinized methodologies?
Empirical Questions
1. What are the different types of routine structures in OSS projects?
2. What factors shape different types of routine structures in OSS projects?
Digital Trace Data
• Extracted from Github (https://developer.github.com/v3/issues/events/) using a 3rd party SQL database (http://www.ghtorrent.org/) and public API (http://octokit.github.io/octokit.rb/)
• Transformed using R• Analyzed using R package TraMineR
http://www.orgdna.net/traminer/
Analysis #1: Cluster Analysis
1. Run Optimal Matching (OM) algorithm on a single project
2. Identify multiple cluster solutions3. Evaluate and choose cluster solution based
on fit statistics4. Characterize each cluster quantitatively5. Qualitative inquiry into routines as text
Analysis #1: OM algorithm
Routine 1: open_issue, edit, mergeRoutine 2: open_issue, edit, close
Routine 3: comment, comment, mergeRoutine 4: comment, comment, comment
Analysis #1: Choosing a Cluster Solution
2 3 4 5 6 7 8 9 100
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
PBCHGASW
Number of Clusters
Exp
lan
ator
y P
ower
Analysis #2: Variation
1. Run optimal matching algorithm on multiple projects
2. Plot distance matrices as heatmaps & calculate average heterogeneity of routines within each project
3. Conduct qualitative inquiry into context using interviews & archival data
Analysis #2: Heat Maps
Red = more homogenous, yellow = more heterogeneous
0.41 (0.25)
0.56 (0.16)
0.62 (0.18)
0.48 (0.25)