The goal of this project was to test operational time performance for each language using as like operations as possible. Though per-lang optimizations could be performed, the systems-level languages allow for inline assembly. That means this would get real nasty, real quick. The implementation is meant to be a naive, or at least a beginner's basic approach to the problem.

The operations are:

• using a struct to contain a billable user account
• propogated by a language provided random number generator
• over a provided (100 default) number of iterations
• propagate a resizeable heap-based account collection of provided operation size (100 default)
• iterate over the list and perform a billing based on account balance (actual values don't matter)
• perform the iteration loop operation number of times
• clear list/free memory

Although variations obviously change between languages, those operations are performed in much the same manner across. The languages are compiled using optimizations where available. C/C++ uses -O2, Rust uses --release, and Zig uses ReleaseFast. Programs will print to command line the total time of execution. As well as the maximum, minimum, and average per-iteration times.

The provided Makefile should build on any machine that has Make/Clang, Rust/Cargo, Zig, and Java. Python .py file to be run via CLI $ python ./python/main.py. Each program allows for up to two numeric arguments, with the first assigning operations, and the second iterations.

Raw output on an admittedly cheap laptop running 100 operations over 1000 iterations are as follows:

*note: Python timed via interpreter, your times may vary. Please speak to your doctor or a licensed medical professional before attempting Java. Not to be confused with financial advice. Offer void in Utah.