Mining the Software Change Repository of a Legacy Telephony

Ability to predict whether a change in one file may require a change in another can be extremely helpful to a software maintainer. Software change repositories store historic changes applied to a software system. They therefore inherently contain a wealth of information regarding (hidden) interactions between different components of the system, including the files that have changed together in the past. Data mining techniques can be employed to learn from this software change experience. We will report on our research into mining the software change repository of a legacy system to learn a relation that maps file pairs to a value indicating whether changing one may require a change in the other