Neuroscience research depends on the acquisition of data, which, in today's technological age, generally requires the use of software. Despite the widespread need for data acquisition software, there are few standard options available for neuroscience labs. As a result, most labs have custom software written specifically tailored to their experiment requirements. Development of this software often falls to lab members. In this talk, I will describe coding principles to ease the process of maintaining your code. I will provide examples of modifications I have made to the Batista lab system following these principles that have improved the current overall functionality of the system as well as its flexibility for long term use and development.