Solving a polynomial system over a finite field is an NP-complete problem of fundamental importance in both pure and applied mathematics.
In~particular, the security of the so-called multivariate public-key cryptosystems, such as HFE of Patarin and UOV of Kipnis et~al., is based on the postulated hardness of solving quadratic polynomial systems over a finite field.
Lokshtanov et al.~(2017) were the first to introduce a probabilistic algorithm that, in the worst-case, solves a Boolean polynomial system in time $O^{*}(2^{delta n})$, for some $delta in (0, 1)$ depending only on the degree of the system, thus beating the brute-force complexity $O^{*}(2^n)$.
Later, B”jorklund et al.~(2019) and then Dinur~(2021) improved this method and devised probabilistic algorithms with a smaller exponent coefficient $delta$.

We survey the theory behind these probabilistic algorithms, and we illustrate the results that we obtained by implementing them in C.
In~particular, for random quadratic Boolean systems, we estimate the practical complexities of the algorithms and their probabilities of success as their parameters change.

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