Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this numerous software metrics and statistical models have been developed, with a correspondingly large

on how the various defect prediction models are implemented resulting in reduced magnitude of defects.

of heuristics faults while performing software component testing. Finally, high automatic fault localization demand led to the proposal and development of software functionality on predicting the faults at an earlier stage with minimal prediction time. To overcome the defect on software fault localization, Tabu

written in Java 1.4.x and Java 1.5.x to identify the distribution of groups used by developers. We use the data from the study to create prediction models that would allow developers to estimate the number of different groups of classes, fields and methods that are expected to be generated for large Java

Finite-state verification techniques, such as model checking, have shown promise as a cost-effective means for finding defects in hardware designs. To date, the application of these techniques to software has been hindered by several obstacles. Chief among these is the problem of constructing a

unique aspects: it does not require the programmer to annotate the source program (invariants are inferred); it minimizes noise (false error messages) through a process known as "counterexample-driven refinement". SLAM exploits and extends results fi'om program analysis, model checking

the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management

data is also useful for predicting system operation and network failures. Based on over one million 2 Polastre et. al. data readings, we analyze the node and network design and develop network reliability profiles and failure models.

This paper surveys the fundamental principles of subjective Bayesian inference in econometrics and the implementation of those principles using posterior simulation methods. The emphasis is on the combination of models and the development of predictive distributions. Moving beyond conditioning on a

Abstract: Process metrics appear to be an effective addition to software defect prediction models usually built upon product metrics. We present a review of research studies that investigate process metrics in defect prediction. The following process metrics are discussed: Number of Revisions