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is satisfactory because—between the initial variable values (`Xi`) and the final values (`Xi'`)—all variables have a polynomially bounded data-flow (omitting constants):
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`X1' ≤ X2+X3` and `X2' ≤ X2` and `X3' ≤ X3`. pymwp derives this bound automatically ([⯈ demo](https://statycc.github.io/pymwp/demo/#original_paper_example3_1_b.c)).
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`X1' ≤ X2+X3` and `X2' ≤ X2` and `X3' ≤ X3`. pymwp derives this bound automatically ([▶ demo](https://statycc.github.io/pymwp/demo/#original_paper_example3_1_b.c)).
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However, program
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@@ -39,7 +38,7 @@ However, program
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```
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fails the analysis, because `X1` grows exponentially (`X1'` = $2^{\texttt{X2}}$).
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pymwp reports a program is _infinite_ when no polynomial bound can be derived ([⯈ demo](https://statycc.github.io/pymwp/demo/#original_paper_example3_1_d.c)).
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pymwp reports a program is _infinite_ when no polynomial bound can be derived ([▶ demo](https://statycc.github.io/pymwp/demo/#original_paper_example3_1_d.c)).
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pymwp is inspired by [_"A Flow Calculus of mwp-Bounds for Complexity Analysis"_](https://doi.org/10.1145/1555746.1555752).
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