Al-Farg'oniy avlodlari (The descendants of Al-Fargani)
Published December 25, 2024 | Version v2
Journal article Open

Dasturiy ta'minotdagi xatolarni avtomatik topish va tuzatish uchun o'qitiladigan algoritmlar

Creators

  • 1. Muhammad al-Xorazmiy nomidagi TATU Farg'ona filiali assistenti

Description

Ushbu maqolada dasturiy ta'minotdagi xatolarni avtomatik aniqlash va tuzatish jarayonlarini takomillashtirishga qaratilgan o'qitiladigan algoritmlar (machine learning) bo'yicha tadqiqot natijalari keltirilgan. Dasturiy ta'minot ishlab chiqishning barcha bosqichlarida yuzaga keladigan muammolarni minimallashtirish uchun sun'iy intellektning ilg'or texnikalari qo'llanildi. Algoritm modeliga asosan ma'lumotlar tahlili, xatolarni aniqlash va avtomatik tuzatish mexanizmlari integratsiyalandi. Ushbu yondashuv dasturiy tizimlarning sifatini yaxshilash va ishlab chiqish jarayonini optimallashtirishga yordam beradi. Tadqiqotda matematik modellashtirish, mashina o'rganish algoritmlari va dasturiy ta'minot arxitekturasi qamrab olingan

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References

  • Abdollahi, M., & Ghasemi, M. (2021). Machine Learning Approaches for Bug Detection and Fixing in Software Systems. Journal of Software Engineering, 15(4), 200-215.
  • Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer Science & Business Media.
  • Li, Z., Zou, Y., & Hassan, A. (2019). Deep learning-based software bug detection and prediction: A survey. Software Quality Journal, 27(3), 473–502.
  • OWASP Foundation (2023). OWASP Top 10: The Most Critical Security Risks to Web Applications. Retrieved from owasp.org.
  • Vaswani, A., et al. (2017). Attention is All You Need. Advances in Neural Information Processing Systems (NeurIPS).