The FAIR principles of open science (Findable, Accessible, Interoperable, and Reusable) have had transformative effects on modern large-scale computational science. How best to apply the FAIR principles to workflows themselves, and software more generally, is not yet well understood. This work demonstrates that the software engineering concept of technical debt management provides a useful guide for application of those principles to workflows, and in particular that it implies reusability should be considered as `first among equals'. The work constructs novel systems and tools that are based on a new abstraction approach for reusable workflows, with demonstrations for both synthetic workloads and real-world computational biology and machine learning workflows. This makes it easier to selectively reason about and automate the trade-offs across user ease and performance concerns.
