CONTEXT: Assessing software quality at the early stages of the design and development
process is very difficult since most of the software quality characteristics are not directly …

Numerous studies have applied machine learning to the software defect prediction problem,
ie predicting which modules will experience a failure during operation based on software …

We investigate the use of data mining for the analysis of software metric databases, and
some of the issues in this application domain. Software metrics are collected at various …

Estimating software enhancement efforts became a challenging task in software project
management. Recent researches focused on identifying the best machine learning …

Predicting stability in object-oriented (OO) software, ie, the ease with which a software item
evolves while preserving its design, is a key feature for software maintenance. In fact, a well …

Several machine learning algorithms have been used to assess external quality attributes of
software systems. Given a set of metrics that describe internal software attributes (cohesion …

Software quality is defined as the degree to which a software component or system meets
specified requirements and specifications. Assessing software quality in the early stages of …

Predicting stability in object-oriented (OO) software, ie, the ease with which a software item
can evolve while preserving its design, is a key feature for software maintenance. We …

Integration of metrics computation in most popular computer-aided software engineering
(CASE) tools is a marked tendency. Software metrics provide quantitative means to control …

Software systems surround us. Software is a critical component in everything from the family
car through electrical power] systems to military equipment. As software ploys an ever …