| Issue 29: | Micro-benchmarks for project maintenance purposes | |
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I have prototyped a Groovy program that generates a wild Java program. Consider the home page for this project: Worker and Workers. Now imagine a file, BigKahuna.java, that has 10000 of these inner classes, all using variants of Funcito. If we time the compilation of BigKahuna, (e.g. using the Unix 'time' command), we can scientifically measure incremental changes to the code. I could possibly put this into the Gradle build.
Dec 2, 2011
Project Member
#1
codeto...@gmail.com
Dec 2, 2011
Interesting, but as you noted, I am more interested in runtime performance, and specifically execution of functional code generated by Funcito ("myFunction.apply(x)") as opposed to the normal native API function creation. I am not so much interested in the performance of the function creation time ( "functionFor(callsTo().x())" ), as that is a 1-time cost.
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-Priority-Medium Priority-Low
Apr 18, 2012
I will soon start prototyping some changes which have the potential to change function-execution performance. So I have been working in the background in getting some micro-benchmarks built using Google's Caliper tool. So I am renaming and re-casting this Issue to be support for micro-benchmarking for internal use. This of course includes all of the caveats about the dangers of micro-benchmarking being used in the wrong way.
Summary:
Micro-benchmarks for project maintenance purposes
Status: Started Labels: -Priority-Low Priority-High
Apr 18, 2012
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Milestone-R1.1
May 10, 2012
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Status:
CodeComplete
Jul 24, 2012
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Status:
Done
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