Anecdotally, my master thesis on natural language processing was supposed to consist of first reproducing the results of an influential paper (back then) and then hopefully improving upon it by extending the model used.
The paper made it seem like they had been using a standard PCFG parser (which circulated in the research community at the time) to achieve their results. It turned out they hadn't and instead had written a custom one and in fact their results were not reproducible using the standard parser.
What was meant to be a timesaver in terms of engineering (using a standard parser instead of writing your own) turned out to be a massive time sink. It also turned out that by using a custom parser they had unintentionally diverted from a vanilla PCFG (probabilistic context free grammar), or in other words, some implementation details had led to a departure from the assumed underlying theoretical model.
The paper made it seem like they had been using a standard PCFG parser (which circulated in the research community at the time) to achieve their results. It turned out they hadn't and instead had written a custom one and in fact their results were not reproducible using the standard parser.
What was meant to be a timesaver in terms of engineering (using a standard parser instead of writing your own) turned out to be a massive time sink. It also turned out that by using a custom parser they had unintentionally diverted from a vanilla PCFG (probabilistic context free grammar), or in other words, some implementation details had led to a departure from the assumed underlying theoretical model.