Taus 2dcd7895ec Python: Modernise py/mixed-tuple-returns
Removes the dependence on points-to in favour of an approach based on
(local) data-flow.

I first tried a version that used type tracking, as this more accurately
mimics the behaviour of the old query. However, I soon discovered that
there were _many_ false positives in this setup. The main bad pattern I
saw was a helper function somewhere deep inside the code that both
receives and returns an argument that can be tuples with different sizes
and origins. In this case, global flow produces something akin to a
cartesian product of "n-tuples that flow into the function" and
"m-tuples that flow into the function" where m < n.

To combat this, I decided to instead focus on only flow _within_ a given
function (and so local data-flow was sufficient).

Additionally, another class of false positives I saw was cases where the
return type actually witnessed that the function in question could
return tuples of varying sizes. In this case it seems reasonable to not
flag these instances, since they are already (presumably) being checked
by a type checker.

More generally, if you've annotated the return type of the function with
anything (not just `Tuple[...]`), then there's probably little need to
flag it.
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CodeQL

This open source repository contains the standard CodeQL libraries and queries that power GitHub Advanced Security and the other application security products that GitHub makes available to its customers worldwide.

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We welcome contributions to our standard library and standard checks. Do you have an idea for a new check, or how to improve an existing query? Then please go ahead and open a pull request! Before you do, though, please take the time to read our contributing guidelines. You can also consult our style guides to learn how to format your code for consistency and clarity, how to write query metadata, and how to write query help documentation for your query.

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Description
CodeQL: the libraries and queries that power security researchers around the world, as well as code scanning in GitHub Advanced Security
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