STRATEGIC PLANNING IN THE CONTEXT OF COMBINED SOFTWARE TESTING

Abstract

Relevance. Given the rapid development of software engineering practices and the need for cost-effective quality assurance in competitive environments, the relevance of developing strategic planning approaches for combined testing is growing steadily. The object of research is the strategic planning process for combined software testing that integrates multiple testing methodologies through systematic framework implementation, risk assessment, and resource optimization algorithms. Purpose of the article. This study explores strategic planning approaches for combined software testing and assesses their effectiveness across various application domains. The article aims to provide a structured framework for testing strategy integration and evaluate optimization mechanisms for resource allocation in complex testing environments. Research results. A comprehensive Strategic Planning Framework for Combined Software Testing (SPF-CST) was developed, consisting of six interconnected components: context analysis, multi-dimensional risk assessment, AI-driven prioritization, strategy selection, resource optimization, and monitoring systems. Empirical validation across eight industry case studies demonstrates a 35% reduction in defect leakage rates, 28% improvement in testing efficiency, and 45% decrease in regression testing costs. The study revealed that strategic planning significantly enhances testing effectiveness through systematic methodology integration and adaptive resource management. Conclusions. The study demonstrates the effectiveness of risk-based prioritization and mathematical optimization in testing strategy selection. The proposed framework provides practical tools for organizations to implement comprehensive testing strategies while managing resource constraints and project timelines.