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You could use shiny runtime which allows to create a selectInput and to react to changes to this input with renderPlot:

There are few things that need to be fixed.

1. In your handleClick, you are using setSquares((squares) => squares.splice(i, 1, "X")). squares.splice will mutate the state variable squares which one should never do.
2. Also splice doesn't return updated array but

An array containing the deleted elements.

This causes squares from [null, null, null, null, null, null, null, null, null] to [null] causing you board to become blank for a moment. Then your setSquares((squares) => [...squares2]) kicks in from setTimeout making squares back to array making your square values visible again hence, the flash.

1. computersTurnHandler might return undefined in some cases where none of the return statements trigger hence

Uncaught TypeError: squares2 is undefined handleClick Board.js:34

1. You need to prevent user from clicking until your setTimeout is complete else multiple rapid clicks by user will cause inconsistent behaviour.

As for your query

is it acceptable at all to use Promises in that case

Usually situations like these can simply be solved by making use of temporary variable in most cases.

Now the Solution with promise and fixed handleClick and computersTurnHandler is as follows

TL;DR: the C++ code and Numpy do not use the same matrix-multiplication library.

The matrix multiplication of the GSL library is not optimized. On my machine, it runs sequentially, does not use SIMD instructions (SSE/AVX), does not efficiently unroll the loops to perform register tiling. I also suspect it also does not use the CPU cache efficiently due to the lack of tiling. These optimizations are critical to achieve high-performance and widely used in fast linear algebra libraries.

Numpy uses a BLAS library installed on your machine. On many Linux platform, its uses OpenBLAS or the Intel MKL. Both are very fast (they use all the methods described above) and should run in parallel.

You can find which implementation of BLAS is used by Numpy here. On my Linux machine, Numpy use by default CBLAS which internally use OpenBLAS (OpenBLAS is strangely not directly detected by Numpy).

There are many fast parallel BLAS implementations (GotoBLAS, ATLAS, BLIS, etc.). The open-source BLIS library is great because its matrix multiplication is very fast on many different architectures.

As a result, the simplest way to improve your C++ code is to use the cblas_sgemm CBLAS function and link a fast BLAS library like OpenBLAS or BLIS for example.

For more information:

One simple way to see how bad the GSL perform is to use a profiler (like perf on Linux or VTune on Windows). In your case Linux perf, report that >99% of the time is spent in libgslcblas.so (ie. the GSL library). More specifically, most of the execution time is spent in this following assembly loop:

Before running the run-android run command, navigate to the android directory and enter ./gradlew clean command. After that enter the run-android command again.

The icon for your program needs to be a valid .ico file; it can't be just a renamed .png for instance. Source: this post I found when googling the error.

The dump was probably generated on a system with a different C library version.

You can create the missing collation like the existing one:

I switched to TF2 instead of disabling v2 behavior and that has resolved the problem

You say you have extended XWPFDocument with your own createTOC method. So you also could provide a createTOC(org.apache.xmlbeans.XmlCursor cursor) along the lines of insertNewParagraph(org.apache.xmlbeans.XmlCursor cursor). There the cursor determines where the TOC is inserted.

And because of updating the bodyelements lists, the extended XWPFDocument could provide a recreateBodyElementLists method. This method then recreates all necessary bodyelements lists when called.

Complete example to show the principle:

You can avoid the whole problem by running the UPDATE in an explicit transaction that you roll back if something is not right: