I am writing my Master Thesis in Computer Science and am quite desperate. I have been experimenting with a new set of mathematical tools my advisor has done research on.

In the last three month, the experiments did not work well and did not propose the superior results he proposed previously. Even though I use it in a different setting, I expected it to work at least reasonably well.

That it doesn't work should not be a problem to write my thesis. I only need to find the right explanations for it. However, I have not the slightest idea. These tools are a niche topic even in mathematics and I am a computer scientist.

Apart from this, I am afraid only doing an error analysis won't be sufficient for a master thesis. Since these experiments were actually the premise for further modifications and ideas, I am afraid those has become also useless.

  • 3
    What does your advisor think you should do?
    – Bryan Krause
    Sep 20, 2021 at 21:38
  • Too short for a full answer, but this problem is a common motivator for the "stapler thesis".
    – eykanal
    Sep 20, 2021 at 21:48
  • Talk to your advisor. Also have a look at your university's examination criteria. Often, you will have find that the criteria simply state that your thesis contains new information. Also, you are doing a Master, so the bar for 'new information' is a lot lower than a PhD. This information does not have to be positive. It could be negative -- we have tried X, and the thesis documents why X does not work. You may get lots of cites because it potentially helps future authors respond to reviewers who ask for X. Sep 20, 2021 at 22:04
  • Related, almost a duplicate: academia.stackexchange.com/questions/30995/… Sep 21, 2021 at 0:54

1 Answer 1


The general rule is that research is about knowledge not confirming "expected" results. Knowing that something is false or doesn't work is knowledge and it can be very valuable.

Your professor made an hypothesis and you seem to have shown that it is false. That is worth knowing. It doesn't invalidate future work, but requires that you redirect it.

At a deeper level, knowing why something doesn't work is even more valuable. That is possible in fields like math and CS, but less so in things like humanities research where "proof" is elusive.

But an analysis of the why might be within reach and worth a writeup.

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