{"_buckets": {"deposit": "8b77a7f9-7f0b-49b9-96ad-0a077e10cc44"}, "_deposit": {"id": "4595", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4595"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4595", "sets": ["1597824175385", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Utilizing Computational Intelligence to Assist in Software Release Decision", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Defect tracking using computational intelligencemethods is used to predict software readiness in this study. Bycomparing predicted number of faults and number of faultsdiscovered in testing, software managers can decide whether thesoftware are ready to be released or not.Our predictive models can predict: (i) the number of faults(defects), (ii) the amount of code changes required to correct afault and (iii) the amount of time (in minutes) to make the changesin respective object classes using software metrics as independentvariables. The use of neural network model with a genetic trainingstrategy is introduced to improve prediction results for estimatingsoftware readiness in this study.Our prediction model is divided into three parts: (1) predictionmodel for Presentation Logic Tier software components (2)prediction model for Business Tier software components and (3)prediction model for Data Access Tier software components.Existing object-oriented metrics and complexity software metricsare used in the Business Tier neural network based predictionmodel. New sets of metrics have been defined for the PresentationLogic Tier and Data Access Tier. These metrics are validatedusing two sets of real world application data, one set was collectedfrom a warehouse management system and another set wascollected from a corporate information system."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Defect Tracking"}, {"interim": "Predictive Model"}, {"interim": "N-tier Application"}, {"interim": "Software Readiness"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-03-16"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Utilizing Computational Intelligence to Assist in Software Release Decision.pdf", "filesize": [{"value": "74 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 74000.0, "url": {"url": "https://meral.edu.mm/record/4595/files/Utilizing Computational Intelligence to Assist in Software Release Decision.pdf"}, "version_id": "0466937a-038f-485d-bde3-b032afbd4187"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Enginnering Letters", "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": "2007-05"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2514"}, "item_title": "Utilizing Computational Intelligence to Assist in Software Release Decision", "item_type_id": "21", "owner": "1", "path": ["1597824175385"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004595", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-03-16"}, "publish_date": "2020-03-16", "publish_status": "0", "recid": "4595", "relation": {}, "relation_version_is_last": true, "title": ["Utilizing Computational Intelligence to Assist in Software Release Decision"], "weko_shared_id": -1}