Bug and Test Case Tracking: Optimizing Software Quality with Fabric Dashboards
DOI:
https://doi.org/10.32628/CSEIT251112220Keywords:
Software Quality Management, Bug Tracking Systems, Automated Testing, AI-Driven Development, Performance OptimizationAbstract
Fabric Dashboards revolutionizes software quality management by introducing an integrated approach to bug tracking and test case management. This advanced platform seamlessly combines real-time monitoring, automated issue classification, and predictive analytics to streamline the software development lifecycle. Through a sophisticated multi-layered architecture, it enables organizations to detect and resolve defects efficiently while maintaining comprehensive test coverage across critical system components. The solution incorporates AI-driven features for bug triage, test case generation, and cross-project correlation analysis, significantly enhancing team collaboration and development efficiency. By implementing automated alert mechanisms and intelligent resource allocation strategies, Fabric Dashboards help organizations reduce operational disruptions and minimize the financial impact of software defects. The platform's mobile monitoring capabilities and advanced visualization tools ensure continuous system oversight, while its scalable architecture accommodates growing development needs. These capabilities, combined with robust integration patterns and optimized performance strategies, transform how development teams approach quality assurance and defect management in modern software development environments.
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References
D. Harris, "Software Testing: The Financial Impact of Software Defects," 2019. Available: https://www.deeperthanblue.co.uk/financial-impact-of-software-defects/
S. Bhattacharya, et al., "Comparative analysis of bug tracking tools," 2016. Available: https://www.researchgate.net/publication/316888056_Comparative_analysis_of_bug_tracking_tools
M. Wang, et al., "A multi-layered performance analysis for cloud-based topic detection and tracking in Big Data applications," 2018. Available: https://www.researchgate.net/publication/323543865_A_multi-layered_performance_analysis_for_cloud-based_topic_detection_and_tracking_in_Big_Data_applications
C. Gaur, "Data Integration Pattern Types and Implementation for Enterprises," 2024. Available: https://www.xenonstack.com/blog/data-integration-pattern
BrowserStack, "18 Best Bug Tracking Tools in Software Testing in 2024," 2024. Available: https://www.browserstack.com/guide/best-bug-tracking-tools
S. Zaidi, "The Role of Test Case Management in Software Testing," 2024. Available: https://www.opkey.com/blog/the-role-of-test-case-management-in-software-testing
C. Brown, "8 Best Practices for Dashboard Design with Excellent Examples," 2024. Available: https://www.sigmacomputing.com/blog/best-practices-dashboard-design-examples
J. R. C. Jalaman, et al., "Optimizing Operating System Performance through Advanced Memory Management Techniques: A Comprehensive Study and Implementation," 2024. Available: https://www.researchgate.net/publication/381346561_Optimizing_Operating_System_Performance_through_Advanced_Memory_Management_Techniques_A_Comprehensive_Study_and_Implementation
T. Williams, "Assessing the Efficiency of AI-Driven Development: 2 methods of quantitative evaluation of the impact of AI usage in Software Development," 2024. Available: https://www.keypup.io/blog/2-methods-of-quantitative-evaluation-of-the-impact-of-ai-usage-in-software-development
AlgoCademy Blog, "Performance Measurement in Software Development: A Comprehensive Guide," 2024. Available: https://algocademy.com/blog/performance-measurement-in-software-development-a-comprehensive-guide/
A. Bristol, "The Future of AI in Software Development," 2024. Available: https://fortyseven47.com/blog/the-future-of-ai-in-software-development/
R. Garg, "Integrating AI into Software Testing for Test Generation," 2024. Available: https://www.frugaltesting.com/blog/integrating-ai-into-software-testing-for-test-generation
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