A new technique is introduced to generate scattering amplitudes at one loop. Traditional tree algorithms are promoted to generate loop-momentum polynomials called open loops. Combining open loops with tensor-integral and OPP reduction results in a flexible, fast, and numerically stable one-loop generator. This approach allows precise predictions for a wide range of collider processes. Scattering process simulations are crucial for interpreting LHC data. Perturbative calculations beyond leading order are essential to reduce theoretical errors. The LHC's physics program requires NLO predictions for many processes. Traditional one-loop techniques face numerical instabilities and complex algebraic expressions, especially for high multiplicity processes. Recent developments have enabled efficient and stable multi-particle NLO calculations using tensor-integral reduction and Feynman diagrams. New on-shell reductions avoid tensor integrals, reducing one-loop calculations to LO problems. The OPP technique led to highly automatic NLO generators. A trade-off exists between CPU efficiency and automation. Tensor-reduction approaches are fast but limited by large algebraic expressions. OPP-based codes are more flexible but less efficient. A new algorithm is introduced that adapts to both tensor-integral and OPP reduction, maximizing speed and flexibility. The algorithm generates one-loop amplitudes via recursive construction of Feynman diagrams. It handles leading-order amplitudes and virtual NLO corrections as sums of tree and one-loop diagrams. Scattering probabilities and virtual corrections are computed using these amplitudes. Color-stripped tree diagrams are computed recursively by merging sub-trees. Sub-trees are complex n-tuples, and their amplitudes are computed recursively. One-loop amplitudes are computed using loop propagators and numerators that are polynomials in the loop momentum. The numerator is expressed as a polynomial in the loop momentum, and the coefficients are used for both tensor-integral and OPP reduction. The open-loop approach allows efficient computation of scalar-integral coefficients by reducing the problem to a tree-level calculation. The open-loop recursion is further improved by relations from pinching loop propagators. This allows efficient construction of parent and child diagrams. The approach also enables efficient helicity sums by decomposing amplitudes into helicity-dependent coefficients and tensor integrals. A fully automatic generator for QCD corrections to Standard-Model processes was implemented. Diagrams were generated with FEYNARTS, and sub-tree and open-loop topologies were processed with MATHEMATICA. The reduction to scalar integrals was performed using tensor integrals and OPP methods. The method was tested on various processes, showing significant improvements in CPU efficiency and code generation time. The open-loop approach leads to compact codes and fast generation. The CPU cost scales linearly with the number of diagrams, indicating that increasing tensorial rank does not add additional penalties. The results were verified by comparing tensor-integral and OPP reductions, and checking ultraviolet and infrared cancellations. The tensor-reduction approach showed robustness in double precision, with high accuracy forA new technique is introduced to generate scattering amplitudes at one loop. Traditional tree algorithms are promoted to generate loop-momentum polynomials called open loops. Combining open loops with tensor-integral and OPP reduction results in a flexible, fast, and numerically stable one-loop generator. This approach allows precise predictions for a wide range of collider processes. Scattering process simulations are crucial for interpreting LHC data. Perturbative calculations beyond leading order are essential to reduce theoretical errors. The LHC's physics program requires NLO predictions for many processes. Traditional one-loop techniques face numerical instabilities and complex algebraic expressions, especially for high multiplicity processes. Recent developments have enabled efficient and stable multi-particle NLO calculations using tensor-integral reduction and Feynman diagrams. New on-shell reductions avoid tensor integrals, reducing one-loop calculations to LO problems. The OPP technique led to highly automatic NLO generators. A trade-off exists between CPU efficiency and automation. Tensor-reduction approaches are fast but limited by large algebraic expressions. OPP-based codes are more flexible but less efficient. A new algorithm is introduced that adapts to both tensor-integral and OPP reduction, maximizing speed and flexibility. The algorithm generates one-loop amplitudes via recursive construction of Feynman diagrams. It handles leading-order amplitudes and virtual NLO corrections as sums of tree and one-loop diagrams. Scattering probabilities and virtual corrections are computed using these amplitudes. Color-stripped tree diagrams are computed recursively by merging sub-trees. Sub-trees are complex n-tuples, and their amplitudes are computed recursively. One-loop amplitudes are computed using loop propagators and numerators that are polynomials in the loop momentum. The numerator is expressed as a polynomial in the loop momentum, and the coefficients are used for both tensor-integral and OPP reduction. The open-loop approach allows efficient computation of scalar-integral coefficients by reducing the problem to a tree-level calculation. The open-loop recursion is further improved by relations from pinching loop propagators. This allows efficient construction of parent and child diagrams. The approach also enables efficient helicity sums by decomposing amplitudes into helicity-dependent coefficients and tensor integrals. A fully automatic generator for QCD corrections to Standard-Model processes was implemented. Diagrams were generated with FEYNARTS, and sub-tree and open-loop topologies were processed with MATHEMATICA. The reduction to scalar integrals was performed using tensor integrals and OPP methods. The method was tested on various processes, showing significant improvements in CPU efficiency and code generation time. The open-loop approach leads to compact codes and fast generation. The CPU cost scales linearly with the number of diagrams, indicating that increasing tensorial rank does not add additional penalties. The results were verified by comparing tensor-integral and OPP reductions, and checking ultraviolet and infrared cancellations. The tensor-reduction approach showed robustness in double precision, with high accuracy for