Reverse Engineering is an approach to extract requirement information application from XML at higher level of abstraction. In the present study XML to UML transformation methods has been explored and discussed along with some other related work in reverse engineering. A brief review of reverse engineering shows that the transformation results of XML to UML are beneficial for developer. However it does not show changes as per the requirements view. Generation of Natural Language specifications from UML class diagrams is also discussed where results were found encouraging and feasible. All related work of reverse engineering of XML and Natural language specification from UML is clear but a lot of work is to be done to solve real world problems satisfactorily. Capability of different reverse engineering tools is also discussed. Automatic code generation using UML to XML schema transformation is reviewed which shows that it can reduce the time and efforts of coding.
We are living in the era of software and Information technology. Where Reverse engineering has a big role in the up-gradation and maintenance of old software. Precisely if it comes to the reverse engineering of legacy code; so many tools and software are available in the market but still market requirement for reverse engineering of existing codes is unfulfilled. Present paper focus on the various researches published in consecutive years on the same topic. In this study we have covered legacy code and their reverse engineering feasibility as per the cost and time perspective, generation of class diagrams, various problems faced by the different researchers and possible solutions suggested. Conclusion of the study is that we need to do some more experiments to show the class diagram and their relationship and extracting method level dependency while performing reverse engineering of a legacy code by using different language tools and techniques.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.