Bayesian inference for a software reliability model using metrics information.

In this paper, we are concerned with predicting the number of faults N and the time to next failure of a piece of software. Information in the form of software metrics data is used to estimate the prior distribution of N via a Poisson regression model. Given failure time data, and a well known model for software failures, we show how to sample the posterior distribution using Gibbs sampling, as implemented in the package "WinBugs". The approach is illustrated with a practical example

An empirical study of aspect-oriented metrics

Metrics for aspect-oriented software have been proposed and used to investigate the benefits and the disadvantages of crosscutting concerns modularisation. Some of these metrics have not been rigorously defined nor analytically evaluated. Also, there are few empirical data showing typical values of these metrics in aspect-oriented software. In this paper, we provide rigorous definitions, usage guidelines, analytical evaluation, and empirical data from ten open source projects, determining the value of six metrics for aspect-oriented software (lines of code, weighted operations in module, depth of inheritance tree, number of children, crosscutting degree of an aspect, and coupling on advice execution). We discuss how each of these metrics can be used to identify shortcomings in existing aspect-oriented software. (C) 2012 Elsevier B.V. All rights reserved.CNPq [140046/06-2]; Project CNPQ-PROSUL [490478/06-9]; Capes-Grices [2051-05-2]; FAPERGS [10/0470-1]; FCT MCTESinfo:eu-repo/semantics/publishedVersio

Goals/questions/metrics method and SAP implementation projects

During the last years some researchers have studied the critical success factors (CSFs) in ERP implementations. However, until now, no one has studied how these CSFs should be put in practice to help organizations achieve success in ERP implementations. This technical research report attempts to define the usage of Goals/Questions/Metrics (GQM) approach in the definition of a measurement system for ERP implementation projects. GQM approach is a mechanism for defining and interpreting operational, measurable goals. Lately, because of its intuitive nature the approach has gained widespread appeal. We present a metrics overview and a description of GQM approach. Then we provide an example of GQM application for monitoring sustained management support in ERP implementations. Sustained management support is the most cited critical success factor in ERP implementation projects.Postprint (published version

Bayesian inference for fault based software reliability models given software metrics data

We wish to predict the number of faults N and the time to next failure of a piece of software. Software metrics data are used to estimate the prior mean of N via a Poisson regression model. Given failure time data and a some well known fault based models for interfailure times, we show how to sample the relevant posterior distributions via Gibbs sampling using the package Winbugs. Our approach is illustrated with an example

BAYESIAN INFERENCE FOR A SOFTWARE RELIABILITY MODEL USING METRICS INFORMATION.

In this paper, we are concerned with predicting the number of faults N and the time to next failure of a piece of software. Information in the form of software metrics data is used to estimate the prior distribution of N via a Poisson regression model. Given failure time data, and a well known model for software failures, we show how to sample the posterior distribution using Gibbs sampling, as implemented in the package "WinBugs". The approach is illustrated with a practical example.

Predicting Defects in Software Using Grammar-Guided Genetic Programming

The knowledge of the software quality can allow an organization to allocate the needed resources for the code maintenance. Maintaining the software is considered as a high cost factor for most organizations. Consequently, there is need to assess software modules in respect of defects that will arise. Addressing the prediction of software defects by means of computational intelligence has only recently become evident. In this paper, we investigate the capability of the genetic programming approach for producing solution composed of decision rules. We applied the model into four software engineering databases of NASA. The overall performance of this system denotes its competitiveness as compared with past methodologies, and is shown capable of producing simple, highly accurate, tangible rules