AI-Driven Techniques for Noise Filtration in Software Validation Logs
This paper presents a comprehensive examination of the enablement and integration of Natural Language Processing (NLP) and Random Forest Classifier (RFC) techniques to streamline log file diagnostics within a pivotal software development project. This novel integration has significantly improved the accuracy of classifying errors and informational queries in log files, marking a considerable advancement over traditional diagnostic methods. Our approach leverages advanced NLP to efficiently process and interpret the extensive, complex data within log files. In tandem with the robust classification capabilities of RFC, our method identifies and categorizes failure signatures with remarkable precision.
The effectiveness of our methodology and its potential to substantially reduce manual intervention in system diagnostics are underscored by these results. This innovation not only advances the field of software diagnostics into a new era characterized by automation and precision but also establishes a strong foundation for future technological progress. As technology evolves, the insights from this research have the potential to transform the maintenance and reliability of complex computing systems, indicating a significant paradigm shift in the practice of technological diagnostics.
Topics: Natural language processing. Supervised and ensemble machine learning. Software testing.
Tarun Arora
Tarun Arora is working as senior engineer with Intel Technologies Limited, India. He is a seasoned change management and analytics professional with qualified, rich experience working with global teams and Fortune 500 companies across various domains. He has led efforts to drive project management, quality management, customer delivery, business intelligence solutions and handcrafted process automation solutions, and has successfully completed projects with cost savings ranging in the millions of dollars. His technical skills and leadership qualities are trusted by project stakeholders.
He is an Industrial Production Engineering graduate, with continued skills enhancement through various courses, including an Executive Program in Business Intelligence, a Six Sigma Black Belt Certification, a Master of Total Quality Management, Agile Certified Practitioner, etc. -- all supporting a vision of delivering value through service.