Possible Good First Issues

[Emotico]

Hello, we are a group of researchers developing machine learning techniques to locate issues suitable for newcomers, and our model consider the following issues as likely "good first issues"

#11109 #11337 #11751 #11766 #11767 #11770 #9298

May we recommend you to label them as "good first issue" so newcomers know where to choose?

Thank you!

[sigveio]

Hi @wwxu99,

Which researchers / from what organisation/institution would that be?

And I'm curious... what kind of signals are considered?

[Emotico]

Hi @sigveio,

Thanks for your interest. We are researchers from a university and studying open source communities. Our model predicts GFI by considering information such as projects' features, reporters' features, issues' text and comments. We are glad to share further details of this study and interesting results with you when we publish this work. Can you help us check if these issues are good first issues? We would be very grateful and will formally thank you and your team in our work.

[sigveio]

Marking more issues as GFI does have the potential of making projects more accessible to new contributors, so I'm intrigued!

What would you consider the base criteria for a GFI to be? Does it for example include work to triage new issues, such as determining if a bug is actually a bug, or are we talking about actionable issues in the context of producing a pull request that would be accepted / merged into the codebase?

[Emotico]

@sigveio

The GFI mechanism highlights issues in a project that are suitable for newcomers, but does not prevent others from working on the issue. According to our previous research, 40% of the issues marked as GFI are not solved by newcomers, and the more experienced developers are more likely to mislabel GFIs. mislabeling may recommend unsuitable issues to newcomers, preventing them from joining the project and contributing further. Our current research aims to help project maintainers accurately identify and tag issues that are suitable for newcomers, making it less difficult for newcomers to join.
So could you help us check if these issues are good first issues just with your intuition ? We now have a great need for evaluation of the effectiveness of our models.

Thank you!

[sigveio]

#11109 appears to be from an experienced developer who's likely able to implement the features they propose themselves as a first issue. And what they propose should be fairly trivial (likely something similar to #11764).

#11337 while it has a comment from a maintainer and another existing contributor, I'd say the consensus for there being something actionable is relatively low. So this might be a false positive.

#11751 could fall into the criteria of a GFI (non-critical, narrow impact, and probably simple to fix).

#11766 is from an existing contributor and maintainer of a powerful complementing testing framework, so I'd say that has a high probability of being a valid suggestion that can be implemented by the person proposing it. Whether it could be a general GFI I'm not sure of.

#11767 I haven't had the chance to properly look into the validity of this report yet, or the scope of the issue if there is one. The related issues point towards version mismatch in their dependencies / with their package manager. So this might be a false positive.

#11770 like #11109 appears to be from someone who's knowledgable about what they are proposing and would likely be able to implement the feature. As they point out themselves, it might fall outside the scope of what toStrictEqual() is supposed to cover, and be a good candidate for extending with a custom matcher. But at least a warning about it seems reasonable to me, and should be a pretty straight forward first issue if accepted.

#9298 seems stale / outdated. There was another report just the other day in #11765 about this, but it's likely due to using an old version of Jest. That said, it looks like the original issue was fixed as a first contribution. So technically, I suppose the assessment as a GFI is valid in itself.

So to sum up:

Potentially accurate candidates: #11109, #11751, #11766, #11770, #9298*
Possible false positives: #11337, #11767

If they have time, one of the maintainers (e.g. @SimenB) could give you a more accurate judgement.

[Emotico]

@sigveio
Thank you very much!
We look forward to discussing more details with you later, when our work is made public.
Thank you for your support of our work!

[bytrangle]

I enjoy this discussion. Whenever I think of contributing to an open-source project for the first time, I spend an inordinate amount of time sifting through issues to find the most newcomer-friendly one.

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