Applying FAHP to Improve the Performance Evaluation Reliability and Validity of Software Defect Classifiers

Today’s Software complexity makes developing defect-free software almost impossible. On an average, billions of dollars are lost every year because of software defects in the United States alone, while the global loss is much higher. Consequently, developing classifiers to classify software modules into defective and non-defective before software releases, has attracted a great interest in academia and the software industry alike. Although many classifiers have been proposed, none has been proven superior to others. The major reason is that while a research shows that classifier-A is better than classifier-B, we can find other research coming to a diametrically opposite conclusion. These conflicts are usually triggered when researchers report results using their preferred performance quality measures such as recall and precision. Although this approach is valid, it does not examine all possible facets of classifiers’ performance characteristics. Thus, performance evaluation might improve or deteriorate if researchers choose other performance measures. As a result, software developers usually struggle to select the most suitable classifier to use in their projects. The goal of this dissertation is to apply the Fuzzy Analytical Hierarchy Process (FAHP) as a popular multi-criteria decision-making technique to overcome these inconsistencies in research outcomes. This evaluation framework incorporates a wider spectrum of performance measures to evaluate classifiers’ performance, rather than relying on selected, preferred measures. The results show that this approach will increase software developers’ confidence in research outcomes, help them in avoiding false conclusions and indicate reasonable boundaries for them. We utilized 22 popular performance measures and 11 software defect classifiers. The analysis was carried out using KNIME data mining platform and 12 software defect data sets provided by NASA Metrics Data Program (MDP) repository

Applying the FAHP to Improve the Performance Evaluation Reliability of Software Defect Classifiers

Today's software complexity makes developing defect-free software almost impossible. Consequently, developing classifiers to classify software modules into defective and non-defective before software releases have attracted great interest in academia and software industry alike. Although many classifiers have been proposed, no one has been proven superior over others. The major reason is that while a research shows that classifier A is better than classifier B, we can find other research that shows the opposite. These conflicts are usually triggered when researchers report results using their preferable performance evaluation measures such as, recall and precision. Although this approach is valid, it does not examine all possible facets of classifiers performance characteristics. Thus, the performance evaluation might improve or deteriorate if researchers choose other performance measures. As a result, software developers usually struggle to select the most suitable classifier to use in their projects. The goal of this paper is to apply the fuzzy analytical hierarchy process (FAHP) as a popular multicriteria decision-making technique to reliably evaluate classifiers' performance. This evaluation framework incorporates a wider spectrum of performance measures to evaluate classifiers performance rather than relying on selected preferable measures. The results show that this approach will increase software developers' confidence in research outcomes and help them in avoiding false conclusions and infer reasonable boundaries for them. We exploited 22 popular performance measures and 11 software defect classifiers. The analysis was carried out using KNIME data mining platform and 12 software defect data sets provided by the NASA metrics data program (MDP) repository.https://doi.org/10.1109/ACCESS.2019.291596

Implementing Wireless Capsule Endoscopy WCE In Digestive System Diagnostics

The purpose of this research is to discuss the revolutionary endoscopy method WCE that would enhance the diagnostic accuracy and reliability level. Additionally, a comparison has been made with other currently in practice endoscopy methods to single out the strengths and advantages of such endoscopy method. The limitation of this research caused by limited up to date data due to the restrict privacy policy normally adopted by hospitals regarding releasing patients information. This limitation will impose a partially outdated comparison results and conclusions. However, the past trends showed a steady increase in the number of medical facilities that decided to approve the usage of the WCE. These trends are derived from direct interactions with various medical communities. This paper originality and value comes from the fact that increasing number of patients showed a serious reluctant toward continuing all their prescribed medical testing or procedures. Consequently, serious implication can be expected affecting those patients’ health. WCE if understood correctly by both patients and doctors will have a positive impact on the success of diagnostic and treatment statistics