In collaborative software development, program merging is {\\it the} mechanism to integrate changes from multiple programmers. %in modern version control systems. Merge algorithms in modern version control systems report a conflict when changes interfere textually. Merge conflicts require manual intervention and frequently stall modern continuous integration pipelines. Prior work found that, although costly, a large majority of resolutions involve re-arranging text without writing any new code. Inspired by this observation we propose the {\\it first data-driven approach} to resolve merge conflicts with a machine learning model. We realize our approach in a tool \\deepMergeTool{} that uses a novel combination of (i) an edit-aware embedding of merge inputs and (ii) a variation of pointer networks, to construct resolutions from input segments. We also propose an algorithm to localize manual resolutions in a resolved file and employ it to curate a ground-truth dataset comprising 8,719 non-trivial resolutions in JavaScript programs. Our evaluation shows that, on a held out test set, \\deepMergeTool{} can predict correct resolutions for 37\\% of non-trivial merges, compared to only 4\\% by a state-of-the-art semistructured merge technique. Furthermore, on the subset of merges with upto 3 lines (comprising 24\\% of the total dataset), \\deepMergeTool{} can predict correct resolutions with 78\\% accuracy.<\/p>\n","protected":false},"excerpt":{"rendered":"
In collaborative software development, program merging is {\\it the} mechanism to integrate changes from multiple programmers. %in modern version control systems. Merge algorithms in modern version control systems report a conflict when changes interfere textually. Merge conflicts require manual intervention and frequently stall modern continuous integration pipelines. Prior work found that, although costly, a large […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13560],"msr-publication-type":[193715],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[249202,251365],"msr-conference":[],"msr-journal":[259462],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-765124","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-programming-languages-software-engineering","msr-locale-en_us","msr-field-of-study-programming-language","msr-field-of-study-software-engineering"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2022-5-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"IEEE Transactions on Software Engineering (TSE'22)","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/arxiv.org\/abs\/2105.07569v2","label_id":"252679","label":0},{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2022\/07\/deepmerge-tse22.pdf","id":"864546","title":"deepmerge-tse22","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Elizabeth Dinella","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Todd Mytkowicz","user_id":34235,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Todd Mytkowicz"},{"type":"user_nicename","value":"Alexey Svyatkovskiy","user_id":40672,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Alexey Svyatkovskiy"},{"type":"user_nicename","value":"Christian Bird","user_id":31346,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Christian Bird"},{"type":"text","value":"Mayur Naik","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Shuvendu Lahiri","user_id":33640,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Shuvendu Lahiri"}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[144672,144812,144860,733597,776485],"msr_project":[879960,764104],"publication":[],"video":[],"download":[],"msr_publication_type":"article","related_content":{"projects":[{"ID":879960,"post_title":"Future of Program Merge","post_name":"future-of-program-merge","post_type":"msr-project","post_date":"2022-09-22 17:43:06","post_modified":"2022-09-23 16:10:17","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/future-of-program-merge\/","post_excerpt":"We are revisiting the problem of safe program merge and conducting research towards eliminating bad merges (including merge conflicts) of any form by exploring and combining techniques from program verification (for precise formulation of correctness), program synthesis (for automating repeated edits) and machine learning (that includes leveraging pre-trained large language models).","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/879960"}]}},{"ID":764104,"post_title":"Microsoft DeepDev","post_name":"microsoft-deepdev","post_type":"msr-project","post_date":"2021-08-26 09:05:40","post_modified":"2022-04-05 10:10:36","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/microsoft-deepdev\/","post_excerpt":"Microsoft DeepDev is currently in private preview At the Data & AI research team of Microsoft Developer Division (DevDiv), we have the mission of using data and AI to empower every developer and their team to achieve more. 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