The utility of source code, as of other knowledge artifacts, is predicated on the existence of individuals skilled enough to derive value by using or improving it. Developers leaving a software project deprive the project of the knowledge of the decisions they have made. Previous research shows that the survivors and newcomers maintaining abandoned code have reduced productivity and are more likely to make mistakes. We focus on quantifying the extent of abandoned source files and adapt methods from financial risk analysis to assess the susceptibility of the project to developer turnover. In particular, we measure the historical loss distribution and find (1) that projects are susceptible to losses that are more than three times larger than the expected loss. Using historical simulations we find (2) that projects are susceptible to large losses that are over five times larger than the expected loss. We use Monte Carlo simulations of disaster loss scenarios and find (3) that simplistic estimates of the 'truck factor' exaggerate the potential for loss. To mitigate loss from developer turnover, we modify Cataldo et al.'s coordination requirements matrices. We find (4) that we can recommend the correct successor 34% to 48% of the time. We also find that having successors reduces the expected loss by as much as 15%. Our approach helps large projects assess the risk of turnover thereby making risk more transparent and manageable.

The quality of software projects is affected by developer turnover. Mockus studied organizational volatility in the context a large switching software project at Avaya. We replicate his model of the impact of organizational volatility on post-release defects. At the time of Mockus's study, Avaya was experimenting with outsourcing and layoffs were prevalent. In contrast, we study volatility on the Chrome web-browser, which is growing rapidly in terms of popularity and team size. Where possible, we use the same factors as Mockus: the number of co-owners, the number of developers joining and leaving the organization, the number of co-changing directories, developer experience and, instead of LOCs, the churn. Our investigation is conducted at the directory instead of the file level. The control variables, including churn, number of co-owners, and expertise all conform with the consensus in the literature that more changes, more co-owners, and lower expertise lead to an increase in customer reported post-release defects. After normalizing by the highly correlated number of co-owners, the number of developers who leave and join both reduce the number of post-release defects. We discuss this unexpected result.