This article presents a device which is suitable for a practical and efficient implementation of Double Adaptive Quadrature.The device includes local error estimates and attempts to detect the presence of numerical difficulties in the integrand function.If a family of rules with suitable properties is chosen, then this can be achieved without affecting the overall computational cost.Extensive numerical testing has been performed on a comprehensive set of functions showing the effectiveness of the device and its efficiency.

A set of symmetric, closed, interpolatory integration formulas on the interval [-1, 1] with positive weights and increasing degree of precision is introduced. These formulas, called recursive monotone stable (RMS) formulas, allow applying higher order or compound rules without wasting previously computed functional values. An exhaustive search shows the existence of 27 families of RMS formulas, stemming from the simple trapezoidal rule.

Two automatic adaptive integrators from QUADPACK (namely, QAG, and QAGS) are modified by substituting the Gauss-Kronrod rules used for local quadrature with recursive monotone stable (RMS) formulas. Extensive numerical tests, both for one-dimensional and two-dimensional integrals, show that the resulting programs are faster, perform less functional evaluations, and are more suitable

A set of bilinear forms can be evaluated with a multiplicative complexity lower than the rank of the associated tensor by allowing an arbitrarily small error. A topological interpretation of this fact is presented together with the error analysis. A complexity measure is introduced which takes into account the numerical stability of algorithms. Relations are established between the complexities of exact and approximate algorithms.

Bounded integer matrices are matrices whose entries are bounded integers.