Implementation of an Environment to Analyze Object-Oriented Software and Quality Assurance
Devendrasingh Thakore1, Akhilesh R Upadhyay2
1Devendrasingh Thakore, Ph.D Scholar, Department of Computer Network Software Engineering, Shri JJT University, Jhunjhunu, (Rajasthan), India.
2Dr. Akhilesh R Upadhyay, Department of Electronics and Communication Engineering, Vice Principal, Sagar Institute of Research and Technology, Bhopal (M.P), India.
Manuscript received on 10 May 2013 | Revised Manuscript received on 18 May 2013 | Manuscript Published on 30 May 2013 | PP: 236-240 | Volume-2 Issue-6, May 2013 | Retrieval Number: F0856052613/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Software quality cannot be improved simply by following industry standards which require adaptive/upgrading of standards or models very frequently. Quality Assurance (QA) at the design phase, based on typical design artifacts, reduces the efforts to fix the vulnerabilities which affect the cost of product. For this different design metrics are available, based on its result design artifacts can be modified. But to modify or make changes in artifacts is not an easy task because these artifacts are designed by rigorous study of requirements. The purpose of this research work is to automatically find out software artifacts for the system from natural language requirement specification as forward engineering and from source code as reengineering, to generate formal models specification in exportable form that can be used by UML compliment tool to visually represent the model of system. This research work also assess these design models artifacts for quality assurance and suggest alternate designs options based on primary constraints given in requirement specification. Following problems are resolved in this research work 1. Automatic generation of design phase class model from natural language input 2. Automatic generation of design phase class model from already developed source code 3. Generation of secure validated deign from above generated class models with different level of security as high low and medium with the help of different software metrics To resolve these problem there is need of automated environment which will assess generated design artifacts from natural language as forward engineering and from source code as reengineering and finally suggest and validates alternate designs options for better quality assurance.
Keywords: POS Tagging, OOA, UML, Use Case, Actor, Software Quality, Quality Metrics, XMI.
Scope of the Article: Software Engineering & Its Applications