https://github.com/src-d/reading-club
Paper reading club at source{d}
https://github.com/src-d/reading-club
academic-paper reading-group
Last synced: about 1 month ago
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Paper reading club at source{d}
- Host: GitHub
- URL: https://github.com/src-d/reading-club
- Owner: src-d
- License: cc-by-sa-4.0
- Created: 2018-08-23T15:09:41.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-12-10T11:02:18.000Z (about 6 years ago)
- Last Synced: 2025-05-05T05:05:25.430Z (10 months ago)
- Topics: academic-paper, reading-group
- Homepage:
- Size: 112 KB
- Stars: 115
- Watchers: 35
- Forks: 12
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# source{d} paper reading club
Discuss papers at the intersection of Software Engineering, Programming Languages and Machine
Learning communities related to applications of Machine Learning to Code.
## Goal
- promote reading papers
- rise awareness on current research directions in PL, SW, ML communities
- create opportunity for collaborations
## How it works
Every 2 weeks we pick and discuss a paper.
Next paper is chosen from a list of candidates established at the end of the session.
Anyone can comment on a paper's PDF on [GDrive][GDrive] with questions or things that are worth
clarifying.
## When
Every 2 weeks on Fridays at 4pm CET
## Where
- on-line on [zoom](https://zoom.us/), ID of the meeting is `974-346-848`.
- in source{d} office in Madrid
## How to participate
- propose/vote for a paper
- join the session [online, or in office space](#where)
## How to organize
A description of the current organization workflow is maintained in
[`organization-workflow.md`](organization-workflow.md).
## Past papers
- __2019.11.29__ [CodeSearchNet Challenge: Evaluating the State of Semantic Code Search](https://arxiv.org/abs/1909.09436). ([notes](https://docs.google.com/document/d/1hb_nATUjDQYY1MuM6tFe4xMITBsdnV-8b8xRb9tTwDQ/edit))
- __2019.11.15__ [When Deep Learning Met Code Search](https://drive.google.com/file/d/12HDIeEp3XW-Xn8AxhyS5CKzRG7AGgpxt/view). ([notes](https://docs.google.com/document/d/1iDgeC3bU8VnhpZ-26ZMMejjODTJToyowbTsBDeTsH48/edit))
- __2019.10.18__ [Assessing the Generalizability of code2vec Token Embeddings](https://drive.google.com/file/d/1A7weXLY6WdWfh4y6dHQN6L2omlfBMnDP/view?usp=sharing). ([notes](https://docs.google.com/document/d/1jXQVoCSkHtSP4aNZifIr-MAgjosEbd9tuMwmU_5q3DU/edit))
- __2019.10.04__ [The Software Heritage Graph Dataset: Public Software Development Under One Roof](https://drive.google.com/open?id=1Oh9o39aZQjM29JVyvMwxg6ANQ4-MIvIB). Antoine Pietri, first author of the paper joined us. ([notes](https://docs.google.com/document/d/1rRKsDVoPB2AhD-D4rfmozewV985lUB_BZXPvS2MPn0w/edit?usp=sharing))
- __2019.09.20__ [End-to-end Deep Learning of Optimization Heuristics](https://drive.google.com/open?id=1GICPdSQdUK1kd4n7_G38k4qqqLZv2GLn). Chris Cummins, author of the paper joined us. ([notes](https://docs.google.com/document/d/1bejKpsc2YomXA1R7Jc1gFD_2qcDyX5HVedmBDPkyjqc/edit))
- __2019.09.06__ [Topology Adaptive Graph Convolutional Networks](https://drive.google.com/file/d/13IctkSdeUvfvfdpNPzryzbq4646GFwsM/view). ([notes](https://docs.google.com/document/d/1ZkNr9Ah2DCPZWSTBUYmWaAtTrsywUXdao_VVP5vGo3Y/edit))
- __2019.08.09__ [Attention Is All You Need](https://drive.google.com/open?id=1ES0lTYFM60kan4P_9bpeZHkPjrlSG4jl). ([notes](https://docs.google.com/document/d/1c_sVnUNnZa7jAClRKB1S605cuTUO4I7gTM_EOzBUjB0/edit))
- __2019.07.26__ [Aroma: Code Recommendation via Structural Code Search](https://drive.google.com/file/d/1dm5OJFq1j3l-mh4yEzfT163AWiCjosYV/view). ([notes](https://docs.google.com/document/d/1hPPajyOWwstWOezko59IWT13k_UDFPDeSUjlnkECwZQ/edit))
- __2019.07.12__ [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://drive.google.com/file/d/1eX3PlQO3YOeL0Jvrvd4JNmhoDuOoRz5m/view). ([notes](https://docs.google.com/document/d/1djU2TvnuKx-lPmFGSye1gkMGtDVDBNW9gDbE811DELk/edit))
- __2019.06.28__ [Import2vec Learning Embeddings for Software Libraries](https://drive.google.com/file/d/1-5VpkX8xo6x6peeccsxD0AgSxx9i2FYv/view?usp=sharing). ([notes](https://docs.google.com/document/d/1RHTdZi492x1RfHWYq7ATsyJVzGwfKlOD3RfJquV90Rc/edit?usp=sharing))
- __2019.06.21__ [Cross-language clone detection by learning over abstract syntax trees](https://drive.google.com/open?id=1kMEdi1X3veFZp5XuAsa7rIIlLHcP6lSd). Daniel Perez, co-author of the paper joined us! ([notes](https://docs.google.com/document/d/14Nnl0AflmWKfqYeF7c-LA9DB63FzK3Z_vL2x080OHrg/edit))
- __2019.06.14__ [Coloring Big Graphs with AlphaGoZero](https://drive.google.com/file/d/1thJ-NRf47Jo4-z1ThtfbaVFfOrQt3G1i/view). ([notes](https://docs.google.com/document/d/1HjvcyNFCHPlVYCAC21oTMLM1VAfkyozDsoESqB5SOUE/edit))
- __2019.05.31__ [Neural Networks for Modeling Source Code Edits](https://drive.google.com/open?id=1b2VOAHhCXBVbT75weBDpAIKAPfufUVJb) and [Learning to Represent Edits](https://drive.google.com/open?id=1hUcDD2NzCf2Om39sHiTSiyDgRxwHyh1s). ([notes](https://docs.google.com/document/d/1xKzYKY38X-aQh-BFFNXMmb0hD8M9zEqpp10ishV1-Hw/edit))
- __2019.05.17__ [Maybe Deep Neural Networks are the Best Choice for Modeling Source Code](https://drive.google.com/file/d/1ZGS9WCme9UJ8TsH5lYrqHrqvPainrO5Q/view?usp=sharing). ([notes](https://docs.google.com/document/d/1lqn7yYg5pLzaq35v5nJsJX5BsDYxkX-eWqF2KMFJ5Uw/edit?usp=sharing))
- __2019.05.03__ skipped, due to long holidays (moved to the next slot).
- __2019.04.19__ [A Comprehensive Survey on Graph Neural Networks](https://drive.google.com/open?id=1hZ-NM8B-Z4RoiDhoWxOlpj5FVwcRq6tF). ([notes](https://docs.google.com/document/d/1p6pA88njm8OMKcKulsv_mihuzVdsuwtrjMcko97IqNw/edit))
- __2019.04.05__ [How Powerful are Graph Neural Networks?](https://drive.google.com/open?id=1hAWPOVdEWYU3pmb5DJfFRE3Fkah-Z6Hn). ([notes](https://docs.google.com/document/d/1-xEng8w-Zw1sT23Wtxo5etXcEOTsx7q1TYT29nHBkhE/edit))
- __2019.03.22__ [Generative Code Modeling with Graphs](https://drive.google.com/open?id=1SMUy5BEU7v8TltaJI8QoPY69G88I5RzA). ([notes](https://docs.google.com/document/d/1EAERXE2pHhBSj8CgPUQv4p9Luupk1iU17QpehSLiV4I/edit))
- __2019.02.22__ [The Adverse Effects of Code Duplication in Machine Learning Models of Code](https://drive.google.com/file/d/1nbs0MwISrbQENn083DqCu1wu6UMfVSSU/view?usp=sharing). ([notes](https://docs.google.com/document/d/1mqGd1_gT2s8r3bU5GDsQM2nvafdxZnTn6ZkwKdzlZWg/edit?usp=sharing))
- __2019.02.08__ [Structured Neural Summarization](https://drive.google.com/file/d/1DSQDmtQG4uSXdlvKJbsh41HEiJ5cQxdk/view?usp=sharing). ([notes](https://docs.google.com/document/d/17-o6UG5zqvxgFkwLGsXmZO62efcEpRqff53VImpPHTI/edit))
- __2019.01.25__ [Sorting and Transforming Program Repair Ingredients via Deep
Learning Code Similarities](https://drive.google.com/open?id=1MTXvBeQl6ITmMd11F6kYUg2mNixmBPFE).
Martin Monperrus and Matias Martinez, co-authors of the paper joined us! ([notes](https://drive.google.com/open?id=19JibDZBemganPKDw5sINMGY5RY1VaWJTgP9VVksB608))
- __2019.01.11__ [A general reinforcement learning algorithm that masters chess, shogi and Go
through self-play](https://drive.google.com/open?id=1l7AbjYjlsLlKWO7-c9Fhm_9j1z9nqtLK).
([notes](https://docs.google.com/document/d/1jDeUUJO7nRWCmyq4JweheKO5mA8KcJ7ueXo2RusiYbE/edit))
- __2018.12.14__ [Improving Automatic Source Code Summarization via Deep Reinforcement
Learning](https://drive.google.com/open?id=1f8EbbpK7xJn3lYMGqQH_vpz135M40ndY).
([notes](https://drive.google.com/open?id=1gLpc1j-W5t90xxjqj7BZvW3DZzbDTpkFXLxv03B6Tp8))
- __2018.11.30__ [Mining Change Histories for Unknown Systematic
Edits](https://drive.google.com/open?id=1UCX-ayAUB6r8p68vdet4vvVwp9Z_zzpm). Tim Molderez, first
author of the paper, joined us for this session! ([notes](https://docs.google.com/document/d/1uX7YEA5x7vnfnxuKsXIsh356Ko1gH1H5O36eEF9glmc/edit))
- __2018.11.16__ [Deep Learning Type
Inference](https://drive.google.com/file/d/1NApPrysETl6cGN_SyrNB8w9cbFvxmQwc/view). This time
*Earl T. Barr* joined, one of the authors of the paper!
([notes](https://docs.google.com/document/d/16llV5O6G8IWkFeBddaVerXOYOrhU8eVoNZy-HI9tUnw/edit),
[meetup](https://www.meetup.com/MLonCode-Madrid/events/256144491/))
- __2018.11.02__ [Learning to Represent
Edits](https://drive.google.com/drive/folders/1cAzkDW_sXb49gRZvvhVvXu3Wi_84lQdn).
([notes](https://drive.google.com/open?id=19ihAlkuj5I9k1OIAxUDLVOxMtfqPIN2UDYy_NSjcrvU))
- __2018.10.19__ [Relational inductive biases, deep learning, and graph
networks](https://drive.google.com/file/d/1gAOdA8S2E9YbOP3AEaYkK3hFTB5cVBAw/view).
([notes](https://docs.google.com/document/d/1uHNoaL2U00TXfgAWoEOgUzNP8vCW34P1psL01Hc1nNU/edit))
- __2018.10.5__: extra session, [Code Vectors: Understanding Programs Through Embedded Abstracted
Symbolic Traces](https://drive.google.com/open?id=1NyGQXxF2Ctq21wYcMjFWGyW0mwmDrXkD). This time
*Jordan Henkel* joined, one of the authors of the paper!
([notes](https://docs.google.com/document/d/1TjiRzSivxXDDl79Fq4Bs7Ax3Zz7hciRGPKxKrUHFd6I/edit),
[slides](https://docs.google.com/presentation/d/14nGDrAHMIYTb2Ca3X3YmxZsgNdbI1NAkERINaTt-Fgg/edit?usp=sharing))
- __2018.09.28__: [code2seq: Generating Sequences from Structured Representations of
Code](https://drive.google.com/open?id=15Gm3Luz6EafAhhc6P2WIaLclrgkmB7yo) by Uri Alon, Eran Yahav
and Omer Levy.
([notes](https://drive.google.com/open?id=1Qzc4Wy94dF-C1LF0TcBWOoxKJiq0meCtFp26VASSoy4))
- __2018.09.14__: [Learning to Represent Programs with
Graphs](https://drive.google.com/file/d/1Jap8MNLn538yAglTRtN7W4R6wT5z1h6O/view) by Miltiadis
Allamanis, Marc Brockschmidt and Mahmoud Khademi.
([notes](https://docs.google.com/document/d/1DGBgoPsEYt1-XVP4DcxMcv21NNuej_jlX2F4f4zdlh0/edit))
- __2018.08.31__: [Intelligent Code Reviews Using Deep
Learning](https://drive.google.com/open?id=1n8N80S4IIsQBo7SLqsEyflaGjK6XN2Gm) by Anshul Gupta and
Neel Sundaresan.
([notes](https://docs.google.com/document/d/1MbCN7qxRF-keT8evb9X6LL7DToM52tDEQgh1UdUyqkY/edit))
All the past papers we studied are available in the [reading club's GDrive][GDrive].
[GDrive]: https://drive.google.com/open?id=1Xck6Ic2amaZsRxNWOCc7WvgheIBL-hcF