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العنوان
Automatic Programs Annotation Using Deep Learning Techniques /
المؤلف
Abdel Haleem, Ahmed Ramadan Abdel Gawad.
هيئة الاعداد
مشرف / Ahmed Younes Mohamed Abdelmonem
مشرف / Ashraf Said Ahmed Elsayed
مشرف / Mohamed Abdel Rahman Mohamed Abdou
مشرف / Walid Mohamed Rabea Abdel Moez
الموضوع
Deep Learning Programs - Automatic.
تاريخ النشر
2022.
عدد الصفحات
53 p. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
علوم الحاسب الآلي
تاريخ الإجازة
9/6/2022
مكان الإجازة
جامعة الاسكندريه - كلية التمريض - Department of Mathematics and Computer Science
الفهرس
Only 14 pages are availabe for public view

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Abstract

The evolution of programming languages over the past few years has been enormous and impressive. These developments are making programming languages simple for beginners to learn and comprehend. It also increases the experience of software developers. Most experi-enced software engineers also find it difficult to understand written code in a specific language like Java or Python that has no comments describing the code functionality. Considering this, the thesis has introduced a novel approach that has been used to solve various issues in code translation. This approach is based on creating vectors for all the Java method’s keywords and identifiers. The approach is known as pre-trained embedding. It entails preparing the word em-bedding using the ”Splitting Merging” technique.