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# Since the last time a developer executed a test case that passed, the developer modified some source files. The source files may be of the same type or mixed type, same directory or different directory. It shouldn't matter. The framework should be source type and location agnostic. Upon executing the test case again, the result is now a failure. The developer panics. It's only days before the deadline to submit bug patches before the source tree is supposed to be closed for release and the bug is a blocker. The developer doesn't want to be shamed for delaying the release, and the source code is too complex to find the bug in time, so what should they do? Use the delta debugging framework! that's what. How? you may ask. Well keep reading to find out. <small>* scenario may vary.</small>
# The delta debugging framework may require the developer to input two pieces of information. One, the test case/function that used to pass but now fails. It will be used to determine whether the source files with progressive changes passes/fails the test. Two, the date of the last known good version that passed the test case. Because of assumption 4 made above, the source directory and files or name of the developer may not be required.
# Once the developer has inputted the two pieced of information, it will use Bonsai to query the source tree and compile a list of all of the changes to the source files since the inputted date. Another possible step to take is to download the source code from the inputted date, compile the source tree and execute the test case to determine whether or not the version on the inputted date actually passes the test case. Why? Because of the age-old idioms of (1) users are stupid and (2) never trust user input. Of course, if this is done, then step 5.1 would change slightly from removing changes to applying changes.
# (If there was a method of determining change dependencies so as to eliminate the possibility of inconsistencies, it would be done in this step. One possible way of reducing the possibility of inconsistencies is to logically group changes by location or check in time.)
# This step would be where the delta debugging algorithm would come into play. The algorithm should basically:
