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Modern information technologies (IT) play a key role in ensuring the competitiveness of organizations. In this regard, quality management of software and IT services is becoming an important aspect of successful business. The article discusses modern methods and approaches to quality management, including the integration of Agile, DevOps, Lean and Six Sigma into the processes of development and operation of software solutions. Attention is focused on automated testing, the use of quality metrics and risk management in the context of rapid adaptation to market changes. The advantages of using Continuous Integration (CI) and Continuous Delivery (CD) to increase the reliability and speed of software delivery are disclosed. The role of artificial intelligence and machine learning in predicting problems, automating quality control and increasing the accuracy of error diagnostics is substantiated. Examples of successful implementation of monitoring and analytics systems to optimize development and support processes are structured. It is shown that the integration of modern quality management methods allows not only to improve the final product, but also to reduce the cost of error correction, increase customer satisfaction and strengthen the company’s position in the market.

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Modern Methods of Quality Management in Information Technologies

  • 章节

  • 发表日期：

    2026年

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  • Hassan Ali Al-Ababneh,
  • Abeer Alanani,
  • Salem A. S. Alrhaimi,
  • Fahad H. Alshammari,
  • Yousef Alsafadi,
  • Asokan Vasudevan,
  • Suleiman Ibrahim Mohammad

摘要

Modern information technologies (IT) play a key role in ensuring the competitiveness of organizations. In this regard, quality management of software and IT services is becoming an important aspect of successful business. The article discusses modern methods and approaches to quality management, including the integration of Agile, DevOps, Lean and Six Sigma into the processes of development and operation of software solutions. Attention is focused on automated testing, the use of quality metrics and risk management in the context of rapid adaptation to market changes. The advantages of using Continuous Integration (CI) and Continuous Delivery (CD) to increase the reliability and speed of software delivery are disclosed. The role of artificial intelligence and machine learning in predicting problems, automating quality control and increasing the accuracy of error diagnostics is substantiated. Examples of successful implementation of monitoring and analytics systems to optimize development and support processes are structured. It is shown that the integration of modern quality management methods allows not only to improve the final product, but also to reduce the cost of error correction, increase customer satisfaction and strengthen the company’s position in the market.