A Novel Feature Subset Selection Algorithm for Software Defect Prediction
نویسندگان
چکیده
Feature subset selection is the process of choosing a subset of good features with respect to the target concept. A clustering based feature subset selection algorithm has been applied over software defect prediction data sets. Software defect prediction domain has been chosen due to the growing importance of maintaining high reliability and high quality for any software being developed. A software quality prediction model is built using software metrics and defect data collected from a previously developed system release or similar software projects. Upon validation of such a model, it could be used for predicting the fault-proneness of program modules that are currently under development. The proposed clustering based algorithm for feature selection uses minimum spanning tree based method to cluster features. And then the algorithm is applied over four different data sets and its impact is analyzed.
منابع مشابه
Choosing software metrics for defect prediction: an investigation on feature selection techniques
The selection of software metrics for building software quality prediction models is a search-based software engineering problem. An exhaustive search for such metrics is usually not feasible due to limited project resources, especially if the number of available metrics is large. Defect prediction models are necessary in aiding project managers for better utilizing valuable project resources f...
متن کاملA Parallel Genetic Algorithm Based Method for Feature Subset Selection in Intrusion Detection Systems
Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
متن کاملImprovement of effort estimation accuracy in software projects using a feature selection approach
In recent years, utilization of feature selection techniques has become an essential requirement for processing and model construction in different scientific areas. In the field of software project effort estimation, the need to apply dimensionality reduction and feature selection methods has become an inevitable demand. The high volumes of data, costs, and time necessary for gathering data , ...
متن کاملA Novel Approach to Feature Selection Using PageRank algorithm for Web Page Classification
In this paper, a novel filter-based approach is proposed using the PageRank algorithm to select the optimal subset of features as well as to compute their weights for web page classification. To evaluate the proposed approach multiple experiments are performed using accuracy score as the main criterion on four different datasets, namely WebKB, Reuters-R8, Reuters-R52, and 20NewsGroups. By analy...
متن کاملA Parallel Genetic Algorithm Based Method for Feature Subset Selection in Intrusion Detection Systems
Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
متن کامل