Risky files: an approach to focus quality improvement effort

As the development of software products frequently transitions among globally distributed teams, the knowledge about the source code, design decisions, original requirements, and the history of troublesome areas gets lost. A new team faces tremendous challenges to regain that knowledge. In numerous projects we observed that only 1% of project files are involved in more than 60% of the customer reported defects (CFDs), thus focusing quality improvement on such files can greatly reduce the risk of poor product quality. We describe a mostly automated approach that annotates the source code at the file and module level with the historic information from multiple version control, issue tracking, and an organization's directory systems. Risk factors (e.g, past changes and authors who left the project) are identified via a regression model and the riskiest areas undergo a structured evaluation by experts. The results are presented via a web-based tool and project experts are then trained how to use the tool in conjunction with a checklist to determine risk remediation actions for each risky file. We have deployed the approach in seven projects in Avaya and are continuing deployment to the remaining projects as we are evaluating the results of earlier deployments. The approach is particularly helpful to focus quality improvement effort for new releases of deployed products in a resource-constrained environment.