Software requirement elicitation using AI techniques

العناوين الأخرى

استنباط متطلبات البرمجيات باستخدام تقنيات الذكاء الاصطناعي

مقدم أطروحة جامعية

al-Hisah, Rawan

مشرف أطروحة جامعية

al-Harub, Ayish M.
al-Zubaydi, Iyad T.

الجامعة

جامعة الإسراء

الكلية

كلية تكنولوجيا المعلومات

القسم الأكاديمي

قسم هندسة البرمجيات

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2017

الملخص الإنجليزي

The Software Development Life Cycle (SDLC) process is a continuous activity, which encompasses multiple phases.

The most fundamental and essential phase in every SDLC is the requirement engineering phase.

The final output from this phase represents a contract between the customer and the software engineer.

It has been the most important and time-consuming phase since it can determine the success or the failure delivery of the software project.

The requirements are being written in natural language.

Natural language has an ambiguous nature and it is not fully standardized when it comes to the requirements gathering and writing.

The fact that the requirements are written in natural language leads to the conclusion that they might cause some confusion and misunderstanding.

This will be shown and further explained later when the developer defines the table of Software Requirements Specification (SRS).

For the aforementioned reasons, in this thesis, we have developed an Intelligent Software Requirement Analyzer (ISRA) methodology, based on an Artificial Intelligence (AI) technique, that uses the Artificial Neural Network (ANN) to deal with Natural Language Processing (NLP) applications.

Our work’s core function is, tackling the natural language text intelligently and tokenize the requirements’ text.

Ultimately, to have clear and understandable tokens.

The proposed ISRA methodology results show that using it will significantly help, speed-up and enhance the generation a components of SRS .

ISRA has been implemented using MATLAB® Integrated Development Environment (IDE), which offers flexible programming objects for developing Neural Networks (NN), as well as other essential objects and plug-in capabilities.

التخصصات الرئيسية

العلوم الهندسية والتكنولوجية (متداخلة التخصصات)

عدد الصفحات

60

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-896667