{"created":"2020-09-01T15:09:21.553541+00:00","id":4594,"links":{},"metadata":{"_buckets":{"deposit":"cd71f777-377f-4933-af34-d714dd831db0"},"_deposit":{"id":"4594","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4594"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4594","sets":["1582963302567:1597824175385"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Prediction of Software Readiness Using Neural Network","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"In this paper, we explore the behaviour of neuralnetwork in predicting software readiness. Our neural networkmodel aims to predict the number of faults (including objectoriented faults) of a software under development. We use Wardneural network that is a backpropagation network with differentactivation functions. Different activation functions are applied tohidden layer slabs to detect different features in a patternprocessed through a network. In our experiments, hyperbolictangent, Gaussian, Gaussian-complement and linear functions areused as activation functions to improve prediction. This paperalso compares the prediction results from multiple regressionmodel and neural network model. Object-oriented design metricsare used as the independent variables in our study. Our study isconducted on three industrial real-time systems that contain anumber of natural faults that has been reported over a period ofthree years."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Neural Networks"},{"interim":"Object-oriented Design Metrics"},{"interim":"QA in Software Development"},{"interim":"Readiness"},{"interim":"Reliability"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2020-03-16"}],"displaytype":"preview","filename":"Prediction of Software Readiness Using Neural Network.pdf","filesize":[{"value":"66 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4594/files/Prediction of Software Readiness Using Neural Network.pdf"},"version_id":"306c0267-7e28-4bb2-8d09-431e2ba43dc9"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Proceedings of the First International Conference on Information Technology and Applications (ICITA 2002)","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Thwin, Mie Mie Thet"},{"subitem_authors_fullname":"Quah, Tong Seng"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2002"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"1-86467-114-9"},"item_title":"Prediction of Software Readiness Using Neural Network","item_type_id":"21","owner":"1","path":["1597824175385"],"publish_date":"2020-03-16","publish_status":"0","recid":"4594","relation_version_is_last":true,"title":["Prediction of Software Readiness Using Neural Network"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T02:17:59.204588+00:00"}