[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84914-en":3,"doc-seo-84914-105":29,"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":20,"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":13,"seo_description":14,"update_tm":27,"read_time":28},84914,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Domain-Driven Design in Practice: Open-Source Ecosystem Empirical Characterisation","Domain-Driven Design (DDD) has become a leading paradigm for managing software complexity, yet academic work often stays theoretical or anecdotal and many studies lack rigorous empirical evaluation. This study delivers the first large-scale characterisation of DDD in the GitHub open-source ecosystem. Using a Mining Software Repositories approach and a GPT-4o semantic validation pipeline, the work builds a high-fidelity dataset of 2,502 verified repositories and analyzes adoption, architecture patterns, and domain traceability gaps.","Graphical Abstract  \nDomain-Driven Design in Practice: A Large-Scale Empirical Characterisation of the Open-Source Ecosystem  \nOzan Özkan, Önder Babur, Mark van den Brand  \narXiv :2607 .0647 1v 1 [ cs . SE] 7 Jul 2026  \nHighlights  \nDomain-Driven Design in Practice: A Large-Scale Empirical Characterisation of the Open-Source Ecosystem  \nOzan Özkan, Önder Babur, Mark van den Brand  \n• We characterise DDD across 2,502 verified open-source GitHub repositories  \n• An agentic GPT-4o pipeline reaches Cohen’s k=0 .77 against expert labelling  \n• DDD adoption accelerates sharply after a 2017 inflection point  \n• C\\# (34%) and TypeScript (18%) lead practical DDD, not Java (16%)  \n• 25.3% of DDD projects record no explicit business domain in metadata  \nDomain-Driven Design in Practice: A Large-Scale Empirical Characterisation of the Open-Source  \nEcosystem  \nOzan Özkana , Önder Babura,b , Mark van den Branda  \na Mathematics and Computer Science, Eindhoven University of  \nTechnology, Eindhoven, The Netherlands  \nb Information Technology Group, Wageningen University & Research, Wageningen, The  \nNetherlands  \nAbstract  \nContext: Domain-Driven Design (DDD) has emerged as a dominant paradigm for managing software complexity, yet academic research remains largely confined to theoretical proposals and anecdotal case studies. Our prior research indicates that nearly 39% of DDD studies lack rigorous empirical evaluation, leaving the practical implementation of the paradigm largely unexamined at scale.  \nObjective: This study aims to provide the first large-scale characterisation of the DDD landscape within GitHub open-source ecosystem, establishing a data-driven baseline for how the paradigm is implemented and sustained in practice.  \nMethod: We employed a Mining Software Repositories (MSR) methodology, using a hybrid mining strategy (topics and README keywords) to identify an initial set of 11,742 repositories using DDD. To address the peril of “label noise”, we implemented a novel semantic validation pipeline using GPT-4o with a triplicate majority-vote strategy, yielding a high-fidelity dataset of 2,502 verified repositories. We validated this pipeline against a manually labelled sample and obtained substantial agreement with human experts (κ = 0 .77) .  \nResults: DDD adoption accelerated sharply after an inflection point in 2017, and the resulting projects are notably long-lived as their median lifespan exceeds that of the typical GitHub project by more than an order of magnitude, pointing to sustained, professional-grade engineering rather than short-lived experiments. Layered and Clean Architecture are the dominant  \nstructural patterns, while CQRS and Event Sourcing recur in distributed, data-intensive systems. Notably, the data challenge the Java-centric assumption of much academic work: C\\# and TypeScript, rather than Java, are the leading languages of practical DDD adoption.  \nConclusions: DDD has matured into a stable, professional-grade engineering practice, adopted across a diverse range of languages and application domains. However, a quarter of the projects (25.3%) record no explicit business context in their documentation, revealing a persistent gap between how domain intent is designed and how it is preserved in version-controlled artifacts. We argue for lightweight architectural traceability standards to close this gap, and we provide practical guidance for teams that reuse these repositories as reference implementations.  \nKeywords: Domain-Driven Design (DDD), Software Architecture, Software Development, Software Repository Mining, Open Source, GitHub  \n1. Introduction  \nThe growing complexity of modern software systems has become one of the defining challenges of contemporary software engineering. Enterprise applications today routinely span thousands of interconnected components, serve millions of concurrent users, and encode intricate business rules that evolve continuously alongside the organisations they support [1] . Em","cbCaiujntiMWb8oI","https://ap.wps.com/l/cbCaiujntiMWb8oI","pdf",1180953,1,48,"English","en",105,"# Abstract\n# Introduction\n## Background and Motivation\n## Study Approach and Validation\n# Results\n## Adoption and Longevity\n## Architectural Patterns\n## Practical Languages and Domain Metadata Gaps\n# Conclusions\n# Keywords","[{\"question\":\"What is the goal of this study on Domain-Driven Design (DDD)?\",\"answer\":\"The study aims to characterize how DDD is implemented and sustained at scale in the GitHub open-source ecosystem, providing a data-driven baseline for practical adoption.\"},{\"question\":\"How were DDD-related repositories identified and validated?\",\"answer\":\"A Mining Software Repositories methodology used topics and README keywords to find an initial set of repositories. A GPT-4o semantic validation pipeline with a triplicate majority-vote strategy produced a verified dataset of 2,502 repositories, validated against a manually labelled sample (κ=0.77).\"},{\"question\":\"What key findings are reported about adoption, architecture, and domain metadata?\",\"answer\":\"DDD adoption accelerates sharply after a 2017 inflection point, and projects are long-lived. Layered and Clean Architecture dominate, while CQRS and Event Sourcing appear in distributed, data-intensive systems. A notable gap remains: 25.3% of DDD projects record no explicit business domain in metadata.\"}]",1784199316,121,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"domain-driven-design-in-practice-open-source-ecosystem-empirical-characterisation","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/domain-driven-design-in-practice-open-source-ecosystem-empirical-characterisation/84914/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the goal of this study on Domain-Driven Design (DDD)?","Question",{"text":75,"@type":76},"The study aims to characterize how DDD is implemented and sustained at scale in the GitHub open-source ecosystem, providing a data-driven baseline for practical adoption.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were DDD-related repositories identified and validated?",{"text":80,"@type":76},"A Mining Software Repositories methodology used topics and README keywords to find an initial set of repositories. A GPT-4o semantic validation pipeline with a triplicate majority-vote strategy produced a verified dataset of 2,502 repositories, validated against a manually labelled sample (κ=0.77).",{"name":82,"@type":73,"acceptedAnswer":83},"What key findings are reported about adoption, architecture, and domain metadata?",{"text":84,"@type":76},"DDD adoption accelerates sharply after a 2017 inflection point, and projects are long-lived. Layered and Clean Architecture dominate, while CQRS and Event Sourcing appear in distributed, data-intensive systems. 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