| dc.contributor.author | Kumara, M. M. C. D | |
| dc.date.accessioned | 2022-03-11T05:30:19Z | |
| dc.date.available | 2022-03-11T05:30:19Z | |
| dc.date.issued | 2021 | |
| dc.identifier.citation | Kumara, M. M. C. D (2021) REPTR: Requirment perspective technology recommendation system . BSc. Dissertation Informatics Institute of Technology | en_US |
| dc.identifier.issn | 2017025 | |
| dc.identifier.uri | http://dlib.iit.ac.lk/xmlui/handle/123456789/910 | |
| dc.description.abstract | " Selection of the technology is the strongest part of any project. Success of the project based on the selection of technology for the project. Technology stack selection should be a wise decision made by an experienced software architect at the beginning of the project otherwise the technologies selected cannot be changed during later phases. Choosing the most suitable technology stack is an essential factor for a project. But due to some reasons that is not an easy task to select the most suitable technology stack. RePTR is the only solution for that problem as it intends to solve that problem by recommending the best technology stack for the project. The RePTR system proposed to recommend technology stack for web applications as well as mobile applications based on the requirements given by the user. The requirements can be given as a requirement specification document or as a list. The proposed system will described about the technologies along with its features and the links to learning platforms. The Interns of IT industry are the main audience of the RePTR system as they are lack of the experience and the knowledge about the technologies. This system also beneficial to the software architects and the developers for the selection of technology stack." | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Artificial Neural Network | en_US |
| dc.subject | Text classification | en_US |
| dc.subject | Technology stack | en_US |
| dc.subject | Natural language Processing | en_US |
| dc.title | REPTR: Requirement perspective technology recommendation system | en_US |
| dc.type | Thesis | en_US |