POST Data Dependency

A seminal 2014 paper from Google noted that dependency debt is noted as a key contributor to code complexity and technical debt in classical software engineering settings. Their studies found that data dependencies in ML systems carry a similar capacity for building debt, but may be more difficult to detect. Code dependencies can be identified via static analysis by compilers and linkers. Without similar tooling for data dependencies, it can be “inappropriately easy” to build large data dependency chains that can be difficult to untangle.