Analysis of Strength and Capabilities of Major Machine Learning Algorithms Used in Software Testing and Quality Assurance

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Dr. Sunil Khilari
Dr. Balasaheb Bhamango
Dr. Tanaji Dabade
Prof. Ravi Kale
Prof. Asmita Hendre
Dr. Zarina Shaikh


As an Information Technology researchers , it is significant that we have a understand and analyze what’s going on “under the cover” , when utilizing easy-to apply Machine Learning Algorithms, libraries, rather than simply plugging and keep going through fit-predict software quality. his research study take an descriptive analytics of the major machine learning algorithms and their strength and capabilities and all the applications and deployment tools that make it easier to present software project metrics to end-users of both Software Quality Experts and Leads .Here researcher is studying how to extract hidden insight from data and use for analyzing software project metrics Further researcher does the analysis of various Machine learning algorithms used for prioritising algorithm aspects for software project metrics, such as code complexity, predict project completion date and developer productivity etc.

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