How COBOL Code Can Benefit from Machine Learning Insight

Did you realize that you, as a software developer, spend about 75% of your time searching through and querying to understand code, fix bugs and make necessary changes? With every change, applications grow increasingly complex, escalating the importance of software development productivity, which is attracting greater attention from the professional community. Whether a startup's leadership is concerned about how much the software development team costs and wants to promote efficiency to get more done with less, or a corporate engineering leader is "shaking out" their teams to improve output, questions about productivity inevitably arise. While some tools can help improve productivity by suggesting what code to write, even as the developer is writing code, software developers still have to use their brains to add new features, fix bugs, implement changes to meet regulatory requirements, address security needs and solve challenging engineering problems. But what if there was a tool that did some of the hardest thinking for you?