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تقييم و تحسين جودة البرمجيات باستخدام منهجية CRISP-DM
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Tishreen University ورقة بحثية
Publication date
2018
fields
Medical Device Engineering
and research's language is
العربية
Authors
علي سليمان( باحث )
Created by
Shamra Editor
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تعتبر هندسة البرمجيات مفهوماً هاماً لتطوير النظم المعلوماتية، و هي أكثر من عملية ترميز أو تشفير للبرامج، حيث تتضمن الجودة و الجدولة و الاقتصاديات و المعرفة لتطبيق المبادئ. ذلك أن البرمجيات عرضه للأخطاء في التصنيع و التشغيل و تحتاج لعمليات التقييم مثلها مثل أي منتج آخر. في هذه الورقة البحثية نقدم تطويراً للنموذج الشلالي التقليدي لهندسة البرمجيات باستخدام منهجية CRISP-DM المصممة أساساً لهندسة نظم استخلاص البيانات بهدف تحسين جودة البرمجيات، حيث تم دراسة تأثير إدخال هذه المنهجية من ناحية تقليل عدد الأخطاء الموجودة في البرمجيات، و تأثيرها على اكتشاف الأخطاء في مرحلة مبكرة من دورة حياة البرمجية. أظهرت النتائج أن استخدام المنهجية المذكورة ساعد علي تقليل عدد الأخطاء الموجودة في البرمجية بعد انتهاء عملية التطوير، كما ساعد في اكتشاف نسبة أكبر من الأخطاء في المراحل المبكرة من دورة حياة البرمجية، و هو ما يساهم في رفع جودة البرمجيات، مقابل عدد منخفض نسبياً من الزيادة في أسطر الكود نتيجة تطبيق المنهجية المقترحة.
Software engineering is an important concept for the development of information systems, which is more than coding or writing of programs, that it includes quality, scheduling, economics and knowledge of the application of principles. Software is subject to errors in manufacturing and operation and needs to be evaluated like any other product. In this research paper, we present a development of the traditional programmatic model of software engineering using the CRISP-DM methodology, which is primarily used in data extraction engineering systems, that aims to improve software quality. We study the effect of introducing this methodology in terms of reducing the number of errors discovered in software and its impact on error detection at an early stage of the software life cycle. The results showed that the use of this methodology helped to reduce the errors discovered in the software after the development process. It also helped to detect a greater percentage of errors in the early stages of the software life cycle, which helps to increase the quality of the software, compared to a relatively low number of lines. Code because of applying the proposed methodology.
References used
Awni Hammouri, Mustafa Hammad, Mohammad Alnabhan, Fatima Alsarayrah, Software Bug Prediction using Machine Learning Approach,(IJACSA) International Journal of Advanced Computer Science and Applications,Vol. 9, No. 2, 2018
Nexhati Alija, Justification of Software Maintenance Costs, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 7, Issue 3,March 2017
Robert J. Shapiro of Sonecon, The U.S. Software Industry: An Engine for Economic Growth and Employment, , The U.S. Software Industry: An Engine for Economic Growth and Employment, SIIA White Pape,2014
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