: Lu Xiao, Yuanfang Cai, Rick Kazman, Ran Mo, Qiong FengVenue
: International Conference on Software EngineeringDate
: May 2016Type of Experiement
: Case StudySample Size
: 7Class/Experience Level
: ProfessionalParticipant Selection
: Chose Apache projects that differed in scale, application domain, length of history, and many other project characteristics.Data Collection Method
This paper presents a test done to measure architectural debt. Architectural debt is similar to technical debt, but deals with how a flawed architecture accrues penalty. The study studies how exactly to identify and measure architectural debt by tracking the development of seven different Apache projects that differed in characteristics. Over the course of the projects, they measured commits, bug reports, and the number of files from beginning to end.
Results showed that a significant amount of overall maintenance effort was consumed by paying "interest" on architectural debts. Also, the top 5 architectural debts in each project consumed a non-trivial portion of the maintenance effort, but only contained a small portion of error-prone files. In conclusion, it helps to find sources of architectural debt early on to cut down on maintenance costs. It also helps to refactor small clusters of files early on, which will greatly decrease the maintenance costs later on.