MASHINALI O‘QITISH ALGORITMLARI YORDAMIDA DASTURIY TA’MINOTDAGI XATOLIKLARNI (BUG) AVTOMATIK BASHORAT QILISH TIZIMLARI
Keywords:
dasturiy ta’minot, mashinali o‘qitish, xatoliklarni bashorat qilish, dastur kodi, Random Forest, SVM, avtomatlashtirilgan sinovAbstract
Ushbu maqolada dasturiy ta’minotni ishlab chiqish jarayonida xatoliklarni (bug) barvaqt aniqlash va bashorat qilish uchun mashinali o‘qitish algoritmlarini qo‘llash masalalari tadqiq etilgan. Tadqiqot doirasida Random Forest, Support Vector Machine (SVM) va Naive Bayes kabi tasniflash modellari ochiq ma’lumotlar bazalarida (NASA dasturiy ta’minot metrikalari) o‘qitildi va ularning aniqlik ko‘rsatkichlari qiyosiy tahlil qilindi. Natijalar shuni ko‘rsatadiki, mashinali o‘qitish modellarini dasturiy ta’minotni sinovdan o‘tkazish (testing) bosqichiga joriy etish orqali vaqt va resurslarni sezilarli darajada tejash hamda kod sifatini oshirish mumkin.
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