With archaic coding techniques, there will be a time when it will be necessary to modernize vulnerable software. However, redeveloping out-of-date code can be a time-consuming task when dealing with a multitude of files. To reduce the amount of reassembly for Fortran-based projects, in this paper, we develop a prototype for automating the manual labor of refactoring individual files. ForDADT (Fortran Dynamic Autonomous Diagnostic Tool) project is a Python program designed to reduce the amount of refactoring necessary when compiling Fortran files. In this paper, we demonstrate how ForDADT is used to automate the process of upgrading Fortran codes, process the files, and automate the cleaning of compilation errors. The developed tool automatically updates thousands of files and builds the software to find and fix the errors using pattern matching and data masking algorithms. These modifications address the concerns of code readability, type safety, portability, and adherence to modern programming practices.
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