{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:09:34Z","timestamp":1750219774896,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":63,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T00:00:00Z","timestamp":1686009600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,6,6]]},"DOI":"10.1145\/3591195.3595275","type":"proceedings-article","created":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T20:32:43Z","timestamp":1686083563000},"page":"43-57","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Dynamic Properties of Heap Allocations using Neural Networks Trained on Static Code: An Intellectual Abstract"],"prefix":"10.1145","author":[{"given":"Christian","family":"Navasca","sequence":"first","affiliation":[{"name":"University of California at Los Angeles, USA"}]},{"given":"Martin","family":"Maas","sequence":"additional","affiliation":[{"name":"Google, USA"}]},{"given":"Petros","family":"Maniatis","sequence":"additional","affiliation":[{"name":"Google, USA"}]},{"given":"Hyeontaek","family":"Lim","sequence":"additional","affiliation":[{"name":"Google, USA"}]},{"given":"Guoqing Harry","family":"Xu","sequence":"additional","affiliation":[{"name":"University of California at Los Angeles, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,6,6]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dandelion Man\u00e9 Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Vi\u00e9gas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/ Software available from tensorflow.org \t\t\t\t  Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dandelion Man\u00e9 Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Vi\u00e9gas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/ Software available from tensorflow.org"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3212695"},{"key":"e_1_3_2_1_3_1","volume-title":"International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=BJOFETxR-","author":"Allamanis Miltiadis","year":"2018","unstructured":"Miltiadis Allamanis , Marc Brockschmidt , and Mahmoud Khademi . 2018 . Learning to Represent Programs with Graphs . In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=BJOFETxR- Miltiadis Allamanis, Marc Brockschmidt, and Mahmoud Khademi. 2018. Learning to Represent Programs with Graphs. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=BJOFETxR-"},{"key":"e_1_3_2_1_4_1","unstructured":"Uri Alon Shaked Brody Omer Levy and Eran Yahav. 2019. code2seq: Generating Sequences from Structured Representations of Code. arxiv:1808.01400. \t\t\t\t  Uri Alon Shaked Brody Omer Levy and Eran Yahav. 2019. code2seq: Generating Sequences from Structured Representations of Code. arxiv:1808.01400."},{"key":"#cr-split#-e_1_3_2_1_5_1.1","unstructured":"Uri Alon Meital Zilberstein Omer Levy and Eran Yahav. 2018. code2vec: Learning Distributed Representations of Code. https:\/\/doi.org\/10.48550\/ARXIV.1803.09473 10.48550\/ARXIV.1803.09473"},{"key":"#cr-split#-e_1_3_2_1_5_1.2","doi-asserted-by":"crossref","unstructured":"Uri Alon Meital Zilberstein Omer Levy and Eran Yahav. 2018. code2vec: Learning Distributed Representations of Code. https:\/\/doi.org\/10.48550\/ARXIV.1803.09473","DOI":"10.1145\/3290353"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/155090.155108"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1167473.1167488"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1180475.1180477"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/504282.504307"},{"key":"e_1_3_2_1_10_1","volume-title":"Enriching Word Vectors with Subword Information. CoRR, abs\/1607.04606","author":"Bojanowski Piotr","year":"2016","unstructured":"Piotr Bojanowski , Edouard Grave , Armand Joulin , and Tom\u00e1s Mikolov . 2016. Enriching Word Vectors with Subword Information. CoRR, abs\/1607.04606 ( 2016 ), arXiv:1607.04606. arxiv:1607.04606 Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tom\u00e1s Mikolov. 2016. Enriching Word Vectors with Subword Information. CoRR, abs\/1607.04606 (2016), arXiv:1607.04606. arxiv:1607.04606"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3302424.3303988"},{"key":"e_1_3_2_1_12_1","volume-title":"Value Profiling and Optimization. Journal of Instruction Level Parallelism, 1","author":"Calder Brad","year":"1999","unstructured":"Brad Calder , Peter Feller , and Alan Eustace . 1999. Value Profiling and Optimization. Journal of Instruction Level Parallelism, 1 ( 1999 ). Brad Calder, Peter Feller, and Alan Eustace. 1999. Value Profiling and Optimization. Journal of Instruction Level Parallelism, 1 (1999)."},{"key":"e_1_3_2_1_13_1","unstructured":"Binghong Chen Daniel Tarlow Kevin Swersky Martin Maas Pablo Heiber Ashish Naik Milad Hashemi and Parthasarathy Ranganathan. 2022. Learning to Improve Code Efficiency. arxiv:2208.05297. \t\t\t\t  Binghong Chen Daniel Tarlow Kevin Swersky Martin Maas Pablo Heiber Ashish Naik Milad Hashemi and Parthasarathy Ranganathan. 2022. Learning to Improve Code Efficiency. arxiv:2208.05297."},{"key":"e_1_3_2_1_14_1","volume-title":"AutoFDO: Automatic Feedback-Directed Optimization for Warehouse-Scale Applications. In CGO 2016 Proceedings of the 2016 International Symposium on Code Generation and Optimization","author":"Chen Dehao","year":"2016","unstructured":"Dehao Chen , David Xinliang Li , and Tipp Moseley . 2016 . AutoFDO: Automatic Feedback-Directed Optimization for Warehouse-Scale Applications. In CGO 2016 Proceedings of the 2016 International Symposium on Code Generation and Optimization . New York, NY, USA. 12\u201323. Dehao Chen, David Xinliang Li, and Tipp Moseley. 2016. AutoFDO: Automatic Feedback-Directed Optimization for Warehouse-Scale Applications. In CGO 2016 Proceedings of the 2016 International Symposium on Code Generation and Optimization. New York, NY, USA. 12\u201323."},{"key":"e_1_3_2_1_15_1","unstructured":"Zimin Chen Steve Kommrusch and Martin Monperrus. 2021. Neural Transfer Learning for Repairing Security Vulnerabilities in C Code. arxiv:arXiv:2104.08308. \t\t\t\t  Zimin Chen Steve Kommrusch and Martin Monperrus. 2021. Neural Transfer Learning for Repairing Security Vulnerabilities in C Code. arxiv:arXiv:2104.08308."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/512529.512554"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/945885.945892"},{"key":"e_1_3_2_1_18_1","unstructured":"Fran\u00e7ois Chollet. 2015. Keras. https:\/\/keras.io \t\t\t\t  Fran\u00e7ois Chollet. 2015. Keras. https:\/\/keras.io"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2887746.2754181"},{"key":"e_1_3_2_1_20_1","volume-title":"Advances in Neural Information Processing Systems","author":"Cohn David","year":"1996","unstructured":"David Cohn and Satinder Singh . 1996. Predicting Lifetimes in Dynamically Allocated Memory . In Advances in Neural Information Processing Systems , M.C. Mozer, M. Jordan, and T. Petsche (Eds.). 9, MIT Press . https:\/\/proceedings.neurips.cc\/paper\/ 1996 \/file\/a9078e8653368c9c291ae2f8b74012e7-Paper.pdf David Cohn and Satinder Singh. 1996. Predicting Lifetimes in Dynamically Allocated Memory. In Advances in Neural Information Processing Systems, M.C. Mozer, M. Jordan, and T. Petsche (Eds.). 9, MIT Press. https:\/\/proceedings.neurips.cc\/paper\/1996\/file\/a9078e8653368c9c291ae2f8b74012e7-Paper.pdf"},{"key":"e_1_3_2_1_21_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805.","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805."},{"key":"e_1_3_2_1_22_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning, Doina Precup and Yee Whye Teh (Eds.) (Proceedings of Machine Learning Research","volume":"998","author":"Devlin Jacob","year":"2017","unstructured":"Jacob Devlin , Jonathan Uesato , Surya Bhupatiraju , Rishabh Singh , Abdel rahman Mohamed , and Pushmeet Kohli . 2017 . RobustFill: Neural Program Learning under Noisy I\/O . In Proceedings of the 34th International Conference on Machine Learning, Doina Precup and Yee Whye Teh (Eds.) (Proceedings of Machine Learning Research , Vol. 70). PMLR, 990\u2013 998 . https:\/\/proceedings.mlr.press\/v70\/devlin17a.html Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju, Rishabh Singh, Abdel rahman Mohamed, and Pushmeet Kohli. 2017. RobustFill: Neural Program Learning under Noisy I\/O. In Proceedings of the 34th International Conference on Machine Learning, Doina Precup and Yee Whye Teh (Eds.) (Proceedings of Machine Learning Research, Vol. 70). PMLR, 990\u2013998. https:\/\/proceedings.mlr.press\/v70\/devlin17a.html"},{"key":"e_1_3_2_1_23_1","unstructured":"Patrick Fernandes Miltiadis Allamanis and Marc Brockschmidt. 2021. Structured Neural Summarization. arxiv:1811.01824. \t\t\t\t  Patrick Fernandes Miltiadis Allamanis and Marc Brockschmidt. 2021. Structured Neural Summarization. arxiv:1811.01824."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/1134760.1134780"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/217839.217848"},{"key":"e_1_3_2_1_26_1","first-page":"70","article-title":"Autophase: Juggling hls phase orderings in random forests with deep reinforcement learning","volume":"2","author":"Haj-Ali Ameer","year":"2020","unstructured":"Ameer Haj-Ali , Qijing Jenny Huang , John Xiang , William Moses , Krste Asanovic , John Wawrzynek , and Ion Stoica . 2020 . Autophase: Juggling hls phase orderings in random forests with deep reinforcement learning . Proceedings of Machine Learning and Systems , 2 (2020), 70 \u2013 81 . Ameer Haj-Ali, Qijing Jenny Huang, John Xiang, William Moses, Krste Asanovic, John Wawrzynek, and Ion Stoica. 2020. Autophase: Juggling hls phase orderings in random forests with deep reinforcement learning. Proceedings of Machine Learning and Systems, 2 (2020), 70\u201381.","journal-title":"Proceedings of Machine Learning and Systems"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/362422.362476"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3236024.3236051"},{"key":"e_1_3_2_1_29_1","volume-title":"Global Relational Models of Source Code. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=B1lnbRNtwr","author":"Hellendoorn Vincent J.","year":"2020","unstructured":"Vincent J. Hellendoorn , Charles Sutton , Rishabh Singh , Petros Maniatis , and David Bieber . 2020 . Global Relational Models of Source Code. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=B1lnbRNtwr Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, and David Bieber. 2020. Global Relational Models of Source Code. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=B1lnbRNtwr"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/511399.511352"},{"key":"e_1_3_2_1_31_1","volume-title":"Long short-term memory. Neural computation, 9, 8","author":"Hochreiter Sepp","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber . 1997. Long short-term memory. Neural computation, 9, 8 ( 1997 ), 1735\u20131780. Sepp Hochreiter and J\u00fcrgen Schmidhuber. 1997. Long short-term memory. Neural computation, 9, 8 (1997), 1735\u20131780."},{"key":"e_1_3_2_1_32_1","volume-title":"15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21)","author":"Hunter A.H.","year":"2021","unstructured":"A.H. Hunter , Chris Kennelly , Paul Turner , Darryl Gove , Tipp Moseley , and Parthasarathy Ranganathan . 2021 . Beyond malloc efficiency to fleet efficiency: a hugepage-aware memory allocator . In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21) . USENIX Association, 257\u2013273. isbn:978-1-939133-22-9 https:\/\/www.usenix.org\/conference\/osdi21\/presentation\/hunter A.H. Hunter, Chris Kennelly, Paul Turner, Darryl Gove, Tipp Moseley, and Parthasarathy Ranganathan. 2021. Beyond malloc efficiency to fleet efficiency: a hugepage-aware memory allocator. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21). USENIX Association, 257\u2013273. isbn:978-1-939133-22-9 https:\/\/www.usenix.org\/conference\/osdi21\/presentation\/hunter"},{"key":"e_1_3_2_1_33_1","unstructured":"2017. ThinLTO: Scalable and incremental LTO Teresa Johnson Mehdi Amini and Xinliang David Li (Eds.). \t\t\t\t  2017. ThinLTO: Scalable and incremental LTO Teresa Johnson Mehdi Amini and Xinliang David Li (Eds.)."},{"key":"#cr-split#-e_1_3_2_1_34_1.1","unstructured":"Aditya Kanade Petros Maniatis Gogul Balakrishnan and Kensen Shi. 2020. Learning and Evaluating Contextual Embedding of Source Code. https:\/\/doi.org\/10.48550\/ARXIV.2001.00059 10.48550\/ARXIV.2001.00059"},{"key":"#cr-split#-e_1_3_2_1_34_1.2","unstructured":"Aditya Kanade Petros Maniatis Gogul Balakrishnan and Kensen Shi. 2020. Learning and Evaluating Contextual Embedding of Source Code. https:\/\/doi.org\/10.48550\/ARXIV.2001.00059"},{"key":"e_1_3_2_1_35_1","volume-title":"Proceedings of the 37th International Conference on Machine Learning, ICML 2020","author":"Kanade Aditya","year":"2020","unstructured":"Aditya Kanade , Petros Maniatis , Gogul Balakrishnan , and Kensen Shi . 2020 . Learning and evaluating contextual embedding of source code . In Proceedings of the 37th International Conference on Machine Learning, ICML 2020 , 12-18 July 2020 (Proceedings of Machine Learning Research). PMLR. Aditya Kanade, Petros Maniatis, Gogul Balakrishnan, and Kensen Shi. 2020. Learning and evaluating contextual embedding of source code. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 12-18 July 2020 (Proceedings of Machine Learning Research). PMLR."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/2749469.2750392"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/FDL50818.2020.9232934"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3579990.3580010"},{"key":"e_1_3_2_1_39_1","volume-title":"Warm-up Your JVM: Understand and Eliminate JVM Warm-up Overhead in Data-Parallel Systems. In 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16)","author":"Lion David","year":"2016","unstructured":"David Lion , Adrian Chiu , Hailong Sun , Xin Zhuang , Nikola Grcevski , and Ding Yuan . 2016 . Don\u2019 t Get Caught in the Cold , Warm-up Your JVM: Understand and Eliminate JVM Warm-up Overhead in Data-Parallel Systems. In 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16) . USENIX Association, Savannah, GA. 383\u2013400. isbn:978-1-93 1971-33-1 https:\/\/www.usenix.org\/conference\/osdi16\/technical-sessions\/presentation\/lion David Lion, Adrian Chiu, Hailong Sun, Xin Zhuang, Nikola Grcevski, and Ding Yuan. 2016. Don\u2019 t Get Caught in the Cold, Warm-up Your JVM: Understand and Eliminate JVM Warm-up Overhead in Data-Parallel Systems. In 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16). USENIX Association, Savannah, GA. 383\u2013400. isbn:978-1-931971-33-1 https:\/\/www.usenix.org\/conference\/osdi16\/technical-sessions\/presentation\/lion"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/1065010.1065034"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3373376.3378525"},{"key":"e_1_3_2_1_42_1","volume-title":"Effectively Prefetching Remote Memory with Leap. In 2020 USENIX Annual Technical Conference (USENIX ATC 20)","author":"Maruf Hasan Al","year":"2020","unstructured":"Hasan Al Maruf and Mosharaf Chowdhury . 2020 . Effectively Prefetching Remote Memory with Leap. In 2020 USENIX Annual Technical Conference (USENIX ATC 20) . 843\u2013857. Hasan Al Maruf and Mosharaf Chowdhury. 2020. Effectively Prefetching Remote Memory with Leap. In 2020 USENIX Annual Technical Conference (USENIX ATC 20). 843\u2013857."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/1639949.1640102"},{"key":"e_1_3_2_1_44_1","volume-title":"Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation (OSDI\u201916)","author":"Nguyen Khanh","year":"2016","unstructured":"Khanh Nguyen , Lu Fang , Guoqing Xu , Brian Demsky , Shan Lu , Sanazsadat Alamian , and Onur Mutlu . 2016 . Yak: A High-Performance Big-Data-Friendly Garbage Collector . In Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation (OSDI\u201916) . USENIX Association, USA. 349\u2013365. isbn:978 1931971331 Khanh Nguyen, Lu Fang, Guoqing Xu, Brian Demsky, Shan Lu, Sanazsadat Alamian, and Onur Mutlu. 2016. Yak: A High-Performance Big-Data-Friendly Garbage Collector. In Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation (OSDI\u201916). USENIX Association, USA. 349\u2013365. isbn:9781931971331"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3461648.3463844"},{"key":"#cr-split#-e_1_3_2_1_46_1.1","unstructured":"Emilio Parisotto Abdel-rahman Mohamed Rishabh Singh Lihong Li Dengyong Zhou and Pushmeet Kohli. 2016. Neuro-Symbolic Program Synthesis. https:\/\/doi.org\/10.48550\/ARXIV.1611.01855 10.48550\/ARXIV.1611.01855"},{"key":"#cr-split#-e_1_3_2_1_46_1.2","unstructured":"Emilio Parisotto Abdel-rahman Mohamed Rishabh Singh Lihong Li Dengyong Zhou and Pushmeet Kohli. 2016. Neuro-Symbolic Program Synthesis. https:\/\/doi.org\/10.48550\/ARXIV.1611.01855"},{"key":"e_1_3_2_1_47_1","unstructured":"Pardis Pashakhanloo Aaditya Naik Hanjun Dai Petros Maniatis and Mayur Naik. 2022. Learning to Walk over Relational Graphs of Source Code. In Deep Learning for Code (DL4C) Workshop at the International Conference on Learning Representations (ICLR). https:\/\/openreview.net\/forum?id=SubGAoOWJWc \t\t\t\t  Pardis Pashakhanloo Aaditya Naik Hanjun Dai Petros Maniatis and Mayur Naik. 2022. Learning to Walk over Relational Graphs of Source Code. In Deep Learning for Code (DL4C) Workshop at the International Conference on Learning Representations (ICLR). https:\/\/openreview.net\/forum?id=SubGAoOWJWc"},{"key":"e_1_3_2_1_48_1","volume-title":"International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=WQc075jmBmf","author":"Pashakhanloo Pardis","year":"2022","unstructured":"Pardis Pashakhanloo , Aaditya Naik , Yuepeng Wang , Hanjun Dai , Petros Maniatis , and Mayur Naik . 2022 . CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation . In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=WQc075jmBmf Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, and Mayur Naik. 2022. CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=WQc075jmBmf"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"crossref","unstructured":"Michael Pradel and Koushik Sen. 2018. DeepBugs: A Learning Approach to Name-based Bug Detection. arxiv:arXiv:1805.11683. \t\t\t\t  Michael Pradel and Koushik Sen. 2018. DeepBugs: A Learning Approach to Name-based Bug Detection. arxiv:arXiv:1805.11683.","DOI":"10.1145\/3276517"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3306204"},{"key":"#cr-split#-e_1_3_2_1_51_1.1","unstructured":"Nadav Rotem and Chris Cummins. 2021. Profile Guided Optimization without Profiles: A Machine Learning Approach. https:\/\/doi.org\/10.48550\/ARXIV.2112.14679 10.48550\/ARXIV.2112.14679"},{"key":"#cr-split#-e_1_3_2_1_51_1.2","unstructured":"Nadav Rotem and Chris Cummins. 2021. Profile Guided Optimization without Profiles: A Machine Learning Approach. https:\/\/doi.org\/10.48550\/ARXIV.2112.14679"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3368826.3377914"},{"key":"#cr-split#-e_1_3_2_1_53_1.1","unstructured":"Mircea Trofin Yundi Qian Eugene Brevdo Zinan Lin Krzysztof Choromanski and David Li. 2021. MLGO: a Machine Learning Guided Compiler Optimizations Framework. https:\/\/doi.org\/10.48550\/ARXIV.2101.04808 10.48550\/ARXIV.2101.04808"},{"key":"#cr-split#-e_1_3_2_1_53_1.2","unstructured":"Mircea Trofin Yundi Qian Eugene Brevdo Zinan Lin Krzysztof Choromanski and David Li. 2021. MLGO: a Machine Learning Guided Compiler Optimizations Framework. https:\/\/doi.org\/10.48550\/ARXIV.2101.04808"},{"key":"e_1_3_2_1_54_1","unstructured":"Marko Vasic Aditya Kanade Petros Maniatis David Bieber and Rishabh Singh. 2019. Neural Program Repair by Jointly Learning to Localize and Repair. arxiv:arXiv:1904.01720. \t\t\t\t  Marko Vasic Aditya Kanade Petros Maniatis David Bieber and Rishabh Singh. 2019. Neural Program Repair by Jointly Learning to Localize and Repair. arxiv:arXiv:1904.01720."},{"key":"e_1_3_2_1_55_1","volume-title":"Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, and Jakob Uszkoreit.","author":"Vaswani Ashish","year":"2018","unstructured":"Ashish Vaswani , Samy Bengio , Eugene Brevdo , Francois Chollet , Aidan N. Gomez , Stephan Gouws , Llion Jones , \u0141 ukasz Kaiser , Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, and Jakob Uszkoreit. 2018 . Tensor2Tensor for Neural Machine Translation. CoRR , abs\/1803.07416 (2018), arxiv:1803.07416 Ashish Vaswani, Samy Bengio, Eugene Brevdo, Francois Chollet, Aidan N. Gomez, Stephan Gouws, Llion Jones, \u0141 ukasz Kaiser, Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, and Jakob Uszkoreit. 2018. Tensor2Tensor for Neural Machine Translation. CoRR, abs\/1803.07416 (2018), arxiv:1803.07416"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/782814.782850"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/2509136.2509512"},{"key":"e_1_3_2_1_58_1","volume-title":"Proceedings of Machine Learning and Systems, A. Smola, A. Dimakis, and I. Stoica (Eds.). 3, 350\u2013364","author":"Zhou Giulio","year":"2021","unstructured":"Giulio Zhou and Martin Maas . 2021 . Learning on Distributed Traces for Data Center Storage Systems . In Proceedings of Machine Learning and Systems, A. Smola, A. Dimakis, and I. Stoica (Eds.). 3, 350\u2013364 . https:\/\/proceedings.mlsys.org\/paper\/2021\/file\/82161242827b703e6acf9c726942a1e4-Paper.pdf Giulio Zhou and Martin Maas. 2021. Learning on Distributed Traces for Data Center Storage Systems. In Proceedings of Machine Learning and Systems, A. Smola, A. Dimakis, and I. Stoica (Eds.). 3, 350\u2013364. https:\/\/proceedings.mlsys.org\/paper\/2021\/file\/82161242827b703e6acf9c726942a1e4-Paper.pdf"}],"event":{"name":"ISMM '23: 2023 ACM SIGPLAN International Symposium on Memory Management","sponsor":["SIGPLAN ACM Special Interest Group on Programming Languages"],"location":"Orlando FL USA","acronym":"ISMM '23"},"container-title":["Proceedings of the 2023 ACM SIGPLAN International Symposium on Memory Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3591195.3595275","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3591195.3595275","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:31Z","timestamp":1750178251000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3591195.3595275"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,6]]},"references-count":63,"alternative-id":["10.1145\/3591195.3595275","10.1145\/3591195"],"URL":"https:\/\/doi.org\/10.1145\/3591195.3595275","relation":{},"subject":[],"published":{"date-parts":[[2023,6,6]]},"assertion":[{"value":"2023-06-06","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}