The Quality Assurance Engineering (QAE) team at Goldman Sachs was searching for a way to efficiently boost code coverage for legacy code without increasing manual effort, when they found Diffblue Cover. Diffblue Cover uses AI to quickly generate a test suite for legacy Java codebases, allowing engineering teams to focus their efforts on the development of innovative, business-critical new features.
“We decided to use Diffblue Cover because of the potential it offered for helping us meet our most ambitious code coverage targets, while also freeing up developers’ time for the work only they can do,” explains Matt Davey, Managing Director of Technology QAE & SDLC at Goldman Sachs.
Using Diffblue Cover, Goldman Sachs doubled code coverage for the first module from 36% to 72% in less than 10% of the time it would take to do manually. Diffblue Cover created over three thousand high-quality tests overnight; it took just one day to review these generated tests. Compared to the time that would have been required to write the unit tests manually, Diffblue Cover was more than 180 times faster.
Higher code coverage has provided Goldman Sachs’ engineering teams with greater confidence in application stability when adding new code, improving the speed at which the engineering teams can deliver business value. “Diffblue Cover is enabling us to improve quality and build new software, faster,” Matt Davey concludes.
For the full story, check out the case study.