### Lista dei rapporti tecnici dell'anno 1996

 Boraso, M. and Montangero, Carlo and Sedehi, H. Software Cost Estimation: an experimental study of model performances January 26, 2015 UnipiEprints view Download (98Kb) abstract The accurate prediction of software development costs may have a large economic impact. As a consequence, considerable research attention is now directed to understand better the software development process. The objective of this paper is to provide an experimental evaluation of the applicability, universality, and accuracy of some algorithmic software cost estimating models (COCOMO, TUCOMO, PUTNAM, COPMO, ESSE, and Function Points). Data on nine Italian Management Information Systems projects were collected and used to evaluate the performance of the models. The evaluation of the estimates was based on the Mean Magnitude Relative Error and Prediction at level 25% criteria. Results indicated that the models provided interesting performances, better if recalibrated with local data. Gemignani, Luca A Fast Algorithm for Hankel Matrices Represented in Orthogonal Polynomial Bases January 26, 2015 UnipiEprints view Download (85Kb) abstract Consider a $n \times n$ lower triangular matrix $L$ whose $(i+1)$-st row is defined by the coefficients of the real polynomial $p_i(x)$ of degree $i$ such that $\{ p_i(x)\}$ is a set of orthogonal polynomials satisfying a standard three-term recurrence relation. If $H$ is a $n\times n$ real Hankel matrix with nonsingular leading principal submatrices, then $\widehat{H}=L HL^T$ will be referred as a strongly nonsingular Hankel matrix with respect to the orthogonal polynomial basis $\{p_i(x)\}$. In this paper we develop an efficient $O(n^2)$ algorithm for the solution of a system of linear equations with a real symmetric coefficient matrix $\widehat{H}$ which is a Hankel matrix with respect to a suitable orthogonal polynomial basis. We then apply our method to the solution of a weighted finite moment problem. Gemignani, Luca POLYNOMIAL ROOT COMPUTATION BY MEANS OF THE LR ALGORITHM January 26, 2015 UnipiEprints view Download (165Kb) abstract By representing the $LR$ algorithm of Rutishauser and its variants in a polynomial setting, we derive numerical methods for approximating either all of the roots or a number $k$ of the roots of minimum modulus of a given polynomial $p(t)$ of degree $n$. These methods share the convergence properties of the $LR$ matrix iteration but, unlike it, they can be arranged to produce parallel and sequential algorithms which are highly efficient expecially in the case where \$k<

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