Use of relative code churn measures to predict system defect density
North Carolina State University · Microsoft (United States)
Abstract
Software systems evolve over time due to changes in requirements, optimization of code, fixes for security and reliability bugs etc. Code churn, which measures the changes made to a component over a period of time, quantifies the extent of this change. We present a technique for early prediction of system defect density using a set of relative code churn measures that relate the amount of churn to other variables such as component size and the temporal extent of churn.Using statistical regression models, we show that while absolute measures of code churn are poor predictors of defect density, our set of relative measures of code churn is highly predictive of defect density. A case study performed on Windows…
Citation impact
- FWCI
- 53.41
- Percentile
- 100%
- References
- 20
Authors
2Topics & keywords
- Computer science
- Code (set theory)
- Metric (unit)
- Component (thermodynamics)
- Suite
- Set (abstract data type)
- Reliability (semiconductor)
- Software bug
- Reduced inequalities