[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125085-en":3,"doc-seo-125085-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125085,687197207639,"Asher","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms - RCR Report","RCR报告复现了作者在TOSEM论文“A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms”中提出的LAFF方法。文中针对表单输入中的分类字段自动填充需求，说明通过复制包提供可执行脚本以完整复现原论文结果。报告进一步概述LAFF的两阶段流程：离线基于历史实例构建贝叶斯网络，并在输入会话中依据条件依赖进行候选值预测，将高置信度建议提交给用户。","A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms-RCR Report  \n1  \nHICHEM BELGACEM∗ , Luxembourg Institute of Science and Technology, Luxembourg XIAOCHEN LI∗ , Dalian University of Technology, China  \nDOMENICO BIANCULLI, University of Luxembourg, Luxembourg  \nLIONEL BRIAND∗ , Lero SFI Centre for Software Research and University of Limerick, Ireland and University of Ottawa, Canada  \nThis paper represents the Replicated Computational Results (RCR) related to our TOSEM paper “A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms”, where we proposed LAFF, an approach to automatically suggest possible values of categorical fields in data entry forms, which is a common user interface feature in many software systems. In this RCR report, we provide details about our replication package. We make available the different scripts needed to fully replicate the results obtained in our paper.  \nCCS Concepts: • Computing methodologies → Bayesian network models; • Information systems → Recommender systems; • Software and its engineering → Software usability.  \nAdditional Key Words and Phrases: Form filling, Data entry forms, Machine learning, Software data quality, User interfaces  \nACM Reference Format:  \nHichem Belgacem, Xiaochen Li, Domenico Bianculli, and Lionel Briand. 2024. A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms-RCR Report. ACM Trans. Softw. Eng. Methodol.  \n1, 1, Article 1 (January 2024), 7 pages. [https://doi.org/10.1145/3702985](https://doi.org/10.1145/3702985)  \n1 OVERVIEW  \nThis section summarizes the motivation and the contribution of the paper [2] representing the foundation of this RCR report.  \n1.1 Summary of Motivation and Proposed Approach  \nUsers frequently interact with software systems through data entry forms. However, form filling is time-consuming and error-prone. Although several techniques have been proposed to autocomplete or pre-fill fields in the forms, they provide limited support to help users fill categorical fields, i.e., fields that require users to choose the right value among a large set of options.  \n∗ Part of this work was done while the author was affiliated with the University of Luxembourg, Luxembourg.  \nAuthors’ addresses: Hichem Belgacem, Luxembourg Institute of Science and Technology, Luxembourg, hichem.belgacem@ [list.lu](list.lu); Xiaochen Li, Dalian University of Technology, China, [xiaochen.li@dlut.edu.cn](xiaochen.li@dlut.edu.cn); Domenico Bianculli, University of Luxembourg, Luxembourg, [domenico.bianculli@uni.lu](domenico.bianculli@uni.lu); Lionel Briand, Lero SFI Centre for Software Research and University of Limerick, Ireland and University of Ottawa, Canada, [lbriand@uottawa.ca](lbriand@uottawa.ca).  \nPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires [prior specific permission and/or a fee. Request permissions from permissions@acm.org](prior specific permission and/or a fee. Request permissions from permissions@acm.org).  \n© 2024 Copyright held by the owner/author(s) . Publication rights licensed to ACM.  \n1049-331X/2024/1-ART1 $15.00 [https://doi.org/10.1145/3702985](https://doi.org/10.1145/3702985)  \nACM Trans. Softw. Eng. Methodol., Vol. 1, No. 1, Article 1 . Publication date: January 2024 .  \n1:2 Hichem Belgacem, Xiaochen Li, Domenico Bianculli, and Lionel Briand  \nTo address the aforementioned problem, we propose LAFF, a Learning-based Automated Form Filling approach for filling categorical fields in data entry f","cbCaidvHtLGg8Kmq","https://ap.wps.com/l/cbCaidvHtLGg8Kmq","pdf",435451,1,7,"English","en",105,"# Overview\n## Summary of Motivation and Proposed Approach\n## Summary of Results","[{\"question\":\"RCR报告的目的是什么？\",\"answer\":\"该报告对作者在TOSEM论文中提出的LAFF方法进行Replicated Computational Results复现，并提供可用于完整复现结果的复制包与脚本。\"},{\"question\":\"LAFF如何自动为分类字段生成建议？\",\"answer\":\"LAFF包含两阶段：离线的模型构建阶段用依赖分析建立贝叶斯网络；在线的表单填充阶段根据已填写字段的取值及其条件依赖预测候选值，并按置信度对结果进行认可后给出建议列表。\"},{\"question\":\"LAFF的评估涵盖哪些方面？\",\"answer\":\"评估基于五个研究问题，关注整体建议准确性并与现有方法比较、训练与预测的性能开销、局部建模与启发式认可机制对准确性的影响，以及已填字段数量与训练集规模对效果的影响。\"}]","A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms - RCR Report | PDF",1785896541,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-machine-learning-approach-for-automated-filling-of-categorical-fields-in-data-entry-forms-rcr-report","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-machine-learning-approach-for-automated-filling-of-categorical-fields-in-data-entry-forms-rcr-report/125085/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"RCR报告的目的是什么？","Question",{"text":75,"@type":76},"该报告对作者在TOSEM论文中提出的LAFF方法进行Replicated Computational Results复现，并提供可用于完整复现结果的复制包与脚本。","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"LAFF如何自动为分类字段生成建议？",{"text":80,"@type":76},"LAFF包含两阶段：离线的模型构建阶段用依赖分析建立贝叶斯网络；在线的表单填充阶段根据已填写字段的取值及其条件依赖预测候选值，并按置信度对结果进行认可后给出建议列表。",{"name":82,"@type":73,"acceptedAnswer":83},"LAFF的评估涵盖哪些方面？",{"text":84,"@type":76},"评估基于五个研究问题，关注整体建议准确性并与现有方法比较、训练与预测的性能开销、局部建模与启发式认可机制对准确性的影响，以及已填字段数量与训练集规模对效果的影响。","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]