The following sections are included:IntroductionBackgroundApplications of Machine Learning in software testingConclusionsReferences#Introduction#Background#Applications of Machine Learning in software testing#Conclusions#ReferencesARTIFICIAL INTELLIGENCE METHODS FOR SOFTWARE ENGINEERING...
我的Computer Science 专业毕设答辩视频 原标题:Evaluating Machine Learning Approach in the Context of Automatic Test Oracle Generation 摘要:In the field of software testing, test oracle is a mechanism that determines whether software executes correctly with respect to a test case. In industry, human ...
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Machine learning can improve software testing in many ways: Faster and less effortful testing.Old-school testing methods relied almost exclusively on human intervention and manual effort; a group of software engineers and QA testers would run the software manually and scout for any errors. But ...
machine learning techniques, namely those based on decision trees, can uncover the vast majority of those channels while incurring in comparatively lower false positive rates. We also explore the application of semi-supervised and unsupervised machine learning techniques. Our findings suggest that the ...
machine learning techniques that aid in predicting, optimizing, and efficiently learning features. Concurrently, software analysis requires significant time, money, infrastructure, and expertise. As safety-critical software systems advance, the costs and efforts required to ensure their reliability increase ...
Figure 4. Machine Learning process flow. As mentioned before, the idea of this paper is to give a different use of ML compared to a normal flow. A common approach follows the standard way that a dataset is divided into Training Set, Testing Set, and Validation Set; in this case, the ...
The traditional approach to getting started in machine learning has a gap on the path to practitioner. Perhaps you somehow make it to the other side. Looking back, you realize you were not taught one thing about modern software development practices, languages, tooling, or anything that you can...
In the contemporary era, the exploration of machine learning (ML) has gained widespread attention and is being leveraged to augment traditional methodologies in quantitative structure–activity relationship (QSAR) investigations. The principal objective of this research was to assess the anticancer potential...