Implementation of the shift left paradigm: impact on software quality and testing efficiency. Explore Shift Left's impact on software quality & testing efficiency. It cuts defect detection time by 40-60% and elimination costs by 75-85% in software development.
Abstract. The purpose of the study: The study is aimed at determining the impact of the implementation of the Shift Left paradigm on software quality and the efficiency of testing processes in modern software development methodologies. The main goal is to create a comprehensive approach to assessing and optimising the early stages of defect detection through the integration of testing in the initial phases of the software development life cycle. Methods and approaches: The study uses a systematic analysis of scientific literature, an empirical study based on industrial projects, and a comparative analysis of the effectiveness of traditional and Shift Left approaches to testing. Statistical analysis methods are used to process data on the number of defects, time of their detection and cost of their elimination at different stages of development. An experimental evaluation of the integration of automated testing with continuous integration tools is carried out. Results: It is established that the implementation of the Shift Left paradigm leads to a 40-60% reduction in the time of defect detection compared to traditional approaches. A 75-85% reduction in the cost of eliminating defects when they are detected in the early stages of development has been found. The efficiency of automated testing increases by 35-50% when integrated with continuous integration and continuous deployment methodologies. Scientific novelty: For the first time, an integrated approach to assessing the impact of the Shift Left paradigm on complex software quality indicators is proposed through a mathematical model for predicting the effectiveness of early detection of defects. A new methodology for assessing the ROI from the implementation of Shift Left practices has been developed, taking into account the specifics of different types of software projects. Practical significance: The results of the study allow software development organizations to make informed decisions on the implementation of the Shift Left paradigm, optimize testing resources and improve the overall quality of the software product. The proposed methodology can be used to create corporate quality standards and development processes. Prospects: Further research will focus on the integration of artificial intelligence and machine learning into Shift Left processes, the development of self-healing testing systems, and the creation of adaptive quality models for different software domains.
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By Sciaria
By Sciaria
By Sciaria
By Sciaria
By Sciaria
By Sciaria