Survey of Automated Testing Frameworks and Tools for Software Quality Assurance: Challenges and Best Practices

Journal of Artificial Intelligence and Big Data | Vol 2, Issue 1

Table 2. Comparative Analysis of Recent AutomatedTesting Frameworks and Software Quality Assurance Studies

Reference	Study On	Approach	Key Findings	Challenges/ Limitations	Future Directions
Tsuda et al. (2019)	Waseda Software Quality Framework (WSQF)	SQuaRE-based framework for comprehensive product and quality-in-use evaluation	Provides benchmark for software quality; reveals trends, relationships among characteristics, and product context impact	Limited to 21 commercial software products; applicability to broader software unknown	Expand framework to more software types and include dynamic quality metrics
Viriansky and Shaposhnikov (2019)	Automated Quality Management System (AQMS)	AQMS quality determined by design process; considers AQMS and management objects as interrelated information	The effectiveness of AQMS depends on early design stages; establishes goals and quality requirements	Relies heavily on early design; may not adapt easily to late changes	Refine AQMS adaptability and dynamic quality assessment mechanisms
Jharko (2018)	Software quality verification and validation	Analysis of technological process violations, quality definition, and life-cycle software verification	Highlights methods for achieving required software quality through verification and validation	Conceptual; lacks specific implementation details	Develop practical tools to enforce quality at all life-cycle stages
Ibarra and Muñoz (2018)	Quality assurance tools for software development	A tool supporting implementation of QA practices	Promotes and facilitates QA practices; addresses low project success rate (avg. 37%)	Tool adoption and integration challenges in diverse software environments	Broaden tool adoption, integrate AI-based support for QA practices
Liu et al. (2017)	Standardized language for avionics system testing	Allows logical test devices and jump machines to automatically collaborate by introducing device type data and device collaboration actions.	Avionics system testing workflows are altered, and test efficiency is enhanced.	Limited to avionics system context; may need adaptation for other domains	Generalize language for broader industrial system testing
Ma et al. (2016)	BugRocket automated testing platform	Automated testing methods for mobile devices integrated into a distributed testing system	Works for functional and compatibility testing; records failed runs with annotated GUI model and system logs to aid bug fixing	Limited to the 40 most popular Android devices in the study	Extend to more devices, platforms, and broader automated testing scenarios
Zun, Qi and Chen (2016)	MATF (Multi-platform Automatic Testing Framework)	Keyword-driven test technology; encapsulates and expands Appium; integrates test case management, script generation, execution, and reporting	Can automatically parse test cases and generate scripts applicable to both iOS and Android applications	May require further optimization for scalability and complex test scenarios	Enhance multi-platform support, improve efficiency, and support more complex workflows