The impact of code review coverage and code review participation on software quality: a case study of the qt, VTK, and ITK projects

By Shane McIntosh, Yasutaka Kamei, Bram Adams, Ahmed E. Hassan. IEEE Working Conference on Mining Software Repositories, 2014

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CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation (2023, background): “Code Review McIntosh et al. (2014) demonstrated that code review can effectively reduce the defect rate of software.”
The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models (2018, background): “various software metrics on the defect-proneness of a module [9], [10], [11], [12], [13], [14].”
The Impact of Automated Parameter Optimization on Defect Prediction Models (2018, background): “Recent works [73], [89], [90], [98], [143] explore the relationship between modern code review practices and software quality.”
An empirical study of the impact of modern code review practices on software quality (2015, methodology): “The nonlinear style of modelling that we have applied to our datasets is providing significant amounts of explanatory power, leading to more accurately fitting models than our prior work (McIntosh et al. 2014).”
Will They Like This? Evaluating Code Contributions with Language Models (2015, methodology): “To this aim we use language models, which were shown to accurately capture stylistic aspects of code.”