Most dev tools are not yet capable of identifying the specific lines of code that need to be changed, and unearthing that information is hard cognitive work. While some tools can help improve productivity by suggesting what code to write, 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. This can drastically affect productivity and increase the risk of application crashes.
Phase Change President Steve Brothers recently shared his thoughts on how COBOL Colleague offers an elegant solution that uses AI to automate the identification of specific lines of code that require attention to this problem in an article tiled: "How COBOL Code Can Benefit from Machine Learning Insight."
Read the entire article here.
Stephen Tullos is an Analyst with Phase Change Software. You can reach him at [email protected].
How a Novel Approach to AI Mitigates the Need for Comments in Code
October 25, 2022
Code comments are often difficult to understand, incomplete, out of date and untrustworthy to many developers, resulting in significant additional work and unintended business risks. Incorrect documentation results in time and money lost. Transitioning away from relying on developers to add and update comments in code and related documentation requires new methods and tools.
Steve Brothers, President of Phase Change Software, recently addressed this challenge in his article: "How a Novel Approach to AI Mitigates the Need for Comments in Code." He explains how new AI technology can exponentially improve software development productivity by assisting new developers with identifying code behavior and locating the exact place in the code where changes are needed.
Stephen Tullos is an Analyst with Phase Change Software. You can reach him at [email protected].