The hidden cost of code that nobody touches

Engineering organizations face significant challenges with large, aging codebases, often referred to as "big code," which become increasingly difficult to navigate and manage over time. As companies grow, they acquire legacy systems that span multiple version control systems, languages, and dependencies, creating complex environments that can be daunting even for experienced developers. Migration projects aimed at modernizing these codebases are complicated by the need to first locate and understand vast swathes of code, a task hindered by the sheer size and scattered nature of the repositories. Although AI tools promise to accelerate development processes, they too struggle with the limitations of working within large codebases, often missing crucial context and leading to errors that human developers need to catch. Successful navigation and understanding of large codebases, however, can transform migration projects from laborious archaeological endeavors into efficient engineering tasks, significantly reducing the time and effort required to execute them, as demonstrated by companies like MathWorks, which saw drastic improvements in efficiency with enhanced code visibility and search capabilities.