Every profession has deadlines, but the culture of crunch time is particularly prevalent in high-tech fields. The tendency toward and is one of the few things I dislike about computer science and programming. takes time.
Even so, I have found myself buried in crunch time more often than I like to admit. Over the last month, for example, I spent many 10-plus-hour days writing my latest research paper. I was curious how this stretch of time compared to previous research papers'. Now that the deadline has passed, I can satisfy my curiosity by examining the papers' revision control system. It contains every edit made to each of the I was involved in.
The following chart shows how the papers grew as their deadlines approached.
Vertical jumps represent lines added or removed from a paper. Horizontal plateaus represent the length of time between changes. Crunch time is obvious in this diagram: around ten days before a deadline, a paper's growth rate increases, and the length of time between edits decreases. For example, the last ten days of the most recent paper, shown in red, contained about 75% of the paper's total edits.
This number, the fraction of edits in the final ten days, creates an interesting "crunchiness" metric. The following chart shows the metric for each of the papers.
This chart echoes how I would qualitatively rank the papers: "" was easily the most crunchy and "" was the least.
More research is needed to determine if crunchiness correlates with paper acceptance.