Filling the Gap: a Tool to Automate Parameter Estimation for Software Performance Models

© 2015 ACM.Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In this paper we introduce the Filling-the-gap (FG) tool, which automates the parameter estimation of application performance models. This tool implements a set of statistical routines to estimate the parameters of performance models, which are automatically executed using monitoring information kept in a local database

Filling the Gap: a Tool to Automate Parameter Estimation for Software Performance Models

© 2015 ACM.Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In this paper we introduce the Filling-the-gap (FG) tool, which automates the parameter estimation of application performance models. This tool implements a set of statistical routines to estimate the parameters of performance models, which are automatically executed using monitoring information kept in a local database

Filling the Gap: a Tool to Automate Parameter Estimation for Software Performance Models

© 2015 ACM.Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In this paper we introduce the Filling-the-gap (FG) tool, which automates the parameter estimation of application performance models. This tool implements a set of statistical routines to estimate the parameters of performance models, which are automatically executed using monitoring information kept in a local database

Review of Planning for uncertainty: living wills and other advance directives for you and your family, 2nd edition by David John Doukas, M.D., and William Reichel, M.D

Advance directives are useful ways to express one's wishes about end of life care, but even now most people have not completed one of the documents. David Doukas and William Reichel strongly encourage planning for end of life care. Although Planning for Uncertainty is at times fairly abstract for the general reader, it does provide useful background and practical steps

Leibnizian, Galilean and Newtonian structures of spacetime

The following three geometrical structures on a manifold are studied in detail: (1) Leibnizian: a non-vanishing 1-form $\Omega$ plus a Riemannian metric \h on its annhilator vector bundle. In particular, the possible dimensions of the automorphism group of a Leibnizian G-structure are characterized. (2) Galilean: Leibnizian structure endowed with an affine connection $\nabla$ (gauge field) which parallelizes $\Omega$ and \h. Fixed any vector field of observers Z ($\Omega (Z) = 1$), an explicit Koszul--type formula which reconstruct bijectively all the possible $\nabla$'s from the gravitational ${\cal G} = \nabla_Z Z$ and vorticity $\omega = rot Z/2$ fields (plus eventually the torsion) is provided. (3) Newtonian: Galilean structure with \h flat and a field of observers Z which is inertial (its flow preserves the Leibnizian structure and $\omega = 0$). Classical concepts in Newtonian theory are revisited and discussed.Comment: Minor errata corrected, to appear in J. Math. Phys.; 22 pages including a table, Late

Towards a DevOps Approach for Software Quality Engineering

© © 2015 ACM.DevOps is a novel trend in software engineering that aims at bridging the gap between development and operations, putting in particular the developer in greater control of deployment and application runtime. Here we consider the problem of designing a tool capable of providing feedback to the developer on the performance, reliability, and in general quality characteristics of the application at runtime. This raises a number of questions related to what measurement information should be carried back from runtime to designtime and what degrees of freedom should be provided to the developer in the evaluation of performance data. To answer these questions, we describe the design of a filling-the-gap (FG) tool, a software system capable of automatically analyzing performance data either directly or through statistical inference. A natural application of the FG tool is the continuous training of stochastic performance models, such as layered queueing networks, that can inform developers on how to refactor the software architecture

J D Bernal: philosophy, politics and the science of science

This paper is an examination of the philosophical and political legacy of John Desmond Bernal. It addresses the evidence of an emerging consensus on Bernal based on the recent biography of Bernal by Andrew Brown and the reviews it has received. It takes issue with this view of Bernal, which tends to be admiring of his scientific contribution, bemused by his sexuality, condescending to his philosophy and hostile to his politics. This article is a critical defence of his philosophical and political position