… GolnoushAbaei·AliSelamat [19], In this paper many different machine learning techniques
such as decision trees, decision tables, random forest, neural network, Naïve Bayes and …

… importance of software quality with support of machine learning methods … software metric
used for predicting software fault by using … But in this paper, we will focus on machine learning …

… tests to propose a set of software metrics that can be used for … metrics as features to train
supervised machine learning … -level metrics and a second set of method-level metrics that can …

… by software metrics can be best used by machine learning … considers several commonly
used machine learning (ML) … SVM Radial) that are applied on software metrics of all types (eg, …

… software metrics and machine learning techniques. Software metrics play a key role in
measuring software … Metrics control the static information of source code, such as the numbers of …

… software metrics (hereafter, metrics) and machine learning. … by machine learning based on
measurement of metrics without … of a software property that can be used to evaluate software …

… code function level and combined the machine learning algorithm to study the software
metrics for real software. Metrics need to be selected in software metrics, such as the number of …

… design patterns and calculating the metrics for each role. We … effectiveness of machine
learning and software metrics when … metrics in each dataset that supported the machine learning …

… on software metrics and machine learning to identify code smells in an open-source system.
Two feature selection techniques, RFI and IG, were applied on the dataset to find the metrics …

… by analyzing code patterns, and Software Metrics (SMs) can be used to predict … Machine
Learning (ML) to combine alerts from SATs with SMs to predict vulnerabilities in a large software …