Self-adaptive software to unpredicted relevant events
Other Title(s)
التكيف التلقائي للبرمجيات مع الأحداث الخاصة الغير المتوقعة
Dissertant
Thesis advisor
University
Philadelphia University
Faculty
Faculty of Information Technology
Department
Department of Computer Science
University Country
Jordan
Degree
Master
Degree Date
2017
English Abstract
Self-Adaptation software has been used in software development and in lots of organizations to correspond with changing requirements and environments which has been used successfully to deal with planned and predicted problems.
Lots of selfadaptation works rely on bio-inspired approaches dealing with external behaviours but they never dealt with the internal ones.
The idea of modeling both external and internal behaviours along with the integration of predicted and unpredicted events handling is a real actual challenge.
Inspired by the natural genetics, this thesis proposes a solution to the above challenge.
It consists of a self-adaptive software framework integrating both external and internal software behaviours along with predicted and unpredicted events handling.
It models the changeability of the software during the evolutionary lifecycle from a state to another state against planned events (scheduled occurrence: like evolution event) as well as unplanned event (occurring randomly: like faults).
The obtained result, compared to the actual approaches, are valuable
Main Subjects
Information Technology and Computer Science
No. of Pages
43
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Approaches to software feature model based reverse engineering.
Chapter Three : A methodology for software feature based reverse engineering.
Chapter Four : Conclusion and perspictives.
References.
American Psychological Association (APA)
al-Far, Shadha Muhammad. (2017). Self-adaptive software to unpredicted relevant events. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-956232
Modern Language Association (MLA)
al-Far, Shadha Muhammad. Self-adaptive software to unpredicted relevant events. (Master's theses Theses and Dissertations Master). Philadelphia University. (2017).
https://search.emarefa.net/detail/BIM-956232
American Medical Association (AMA)
al-Far, Shadha Muhammad. (2017). Self-adaptive software to unpredicted relevant events. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-956232
Language
English
Data Type
Arab Theses
Record ID
BIM-956232
