A new efficient algorithm for computing Gröbner bases without reduction to zero (F5)

By Jean-Charles Faugère. International Symposium on Symbolic and Algebraic Computation, 2002

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On the complexity of Gröbner basis computation of semi-regular overdetermined algebraic equations (2004, methodology): “We study generic properties of Grobner bases and analyse precisely the behavior of the F5 [ Fau02 ] algorithm.”
Extending SAT Solvers to Cryptographic Problems (2009, methodology): “These equations are then solved and reasoned about with either dedicated equation solvers such as the F5 algorithm [12], or standard SAT solvers.”
Algebraic Cryptanalysis of Hidden Field Equation (HFE) Cryptosystems Using Gröbner Bases (2003, methodology): “This new algorithm replaces AD by a full rank matrix, which is thus minimal (if the input system is regular see [12]).”
Fast and robust numerical solutions to minimal problems for cameras with radial distortion (2008, background): “There exist some attempts to remedy this [5, 6], but for more difficult”
SymPy: Symbolic computing in Python (2017, methodology): “The most common case for the sparse representation is algorithms for computing Gröbner bases (Buchberger, F4, and F5) [7, 11, 12].”