Organizational Volatility and its Effects on Software Defects
https://mockus.org/papers/orgQuality-slides.pdf
Method
"File is the observation unit... One-year prior to tf observation period to obtain predictors... Organizational measures for a file are derived from developers modifying the file during the observation period... Outcome: customer reported defect during prediction period."
Population
"32099 files, 7% with customer defects, 41% of deviance explained"
What it does not show
Single company, one large product. The outcome is field defects at file level, not productivity or morale, and the design cannot rule out reverse causation or a common cause — a struggling area could independently drive both departures and defects.
Audris Mockus
“recent departures from an organization were associated with increased probability of customer-reported defects” after controlling for size, coupling, release count and experience. Notably, the number of newcomers joining was NOT a significant predictor — the cost is in people leaving, not in onboarding.
Tier II: Observational study on real version control, defect and organisational-directory data from a large industrial project, with logistic regression controlling for file size, coupling, release count and developer experience. Correlational, large N.