Add contribution guidelines

Signed-off-by: Vadim Markovtsev <[email protected]>

Author: vmarkovtsev

CODE_OF_CONDUCT.md

@@ -0,0 +1,73 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, gender identity and expression, level of experience,
+education, socio-economic status, nationality, personal appearance, race,
+religion, or sexual identity and orientation.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+* Using welcoming and inclusive language
+* Being respectful of differing viewpoints and experiences
+* Gracefully accepting constructive criticism
+* Focusing on what is best for the community
+* Showing empathy towards other community members
+
+Examples of unacceptable behavior by participants include:
+
+* The use of sexualized language or imagery and unwelcome sexual attention or
+  advances
+* Trolling, insulting/derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or electronic
+  address, without explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned to this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project e-mail
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the project team at [email protected]. All
+complaints will be reviewed and investigated and will result in a response that
+is deemed necessary and appropriate to the circumstances. The project team is
+obligated to maintain confidentiality with regard to the reporter of an incident.
+Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
+
+[homepage]: https://www.contributor-covenant.org

CONTRIBUTING.md

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+# Contributing Guidelines
+
+awesome-machine-learning-on-source-code project is [CC-BY-SA 4.0 licensed](https://creativecommons.org/licenses/by-sa/4.0/) and accepts contributions via GitHub pull requests and twits to [@srcd_](https://twitter.com/srcd_).
+This document outlines some of the conventions on submission workflow, commit message formatting, contact points, and other resources to make it easier to get your contribution accepted.
+
+
+## Support Channels
+
+The official support channels, for both users and contributors, are:
+
+- GitHub [issues](https://github.com/src-d/awesome-machine-learning-on-source-code/issues)*
+- Slack: #machine-learning room in the [source{d} Slack](https://join.slack.com/t/sourced-community/shared_invite/enQtMjc4Njk5MzEyNzM2LTFjNzY4NjEwZGEwMzRiNTM4MzRlMzQ4MmIzZjkwZmZlM2NjODUxZmJjNDI1OTcxNDAyMmZlNmFjODZlNTg0YWM)
+
+*Before opening a new issue or submitting a new pull request, it's helpful to
+search the project - it's likely that another user has already reported the
+issue you're facing, or it's a known issue that we're already aware of.
+
+
+## How to Contribute
+
+Pull Requests (PRs) are the main way to contribute.
+In order for a PR to be accepted it needs to pass a list of requirements:
+
+- Follow the link template*.
+- Be correctly classified as a paper, a blog post, a talk, a software or a dataset.
+- Not be a duplicate.
+- All the PRs have to pass the personal evaluation of at least one of the [maintainers](MAINTAINERS.md).
+
+*Link template:
+
+```
+* [Title](URL) - Description.
+```
+
+Description should not start with "A" or "The". For papers, it should include the authors.
+
+### Format of the commit message
+
+The commit summary must start with "Add" and end with a dot.
+```
+
+### Deprecation
+
+A listed repository should be deprecated if:
+
+* Repository's owner explicitly says that "this library is not maintained".
+* Not committed for long time (2~3 years).
+
+To mark a repository as deprecated, put `[DEPRECATED]` before the title and move it at the bottom of the list.
+

README.md

@@ -106,17 +106,17 @@ A curated list of awesome machine learning frameworks and algorithms that work o
 * [Naturalize](https://github.com/mast-group/naturalize) - Language agnostic framework for learning coding conventions from a codebase and then expoiting this information for suggesting better identifier names and formatting changes in the code. 
 * [Extreme Source Code Summarization](https://github.com/mast-group/convolutional-attention ) - Convolutional attention neural network that learns to summarize source code into a short method name-like summary by just looking at the source code tokens. 
 * [Summarizing Source Code using a Neural Attention Model](https://github.com/sriniiyer/codenn) - CODE-NN, uses LSTM networks with attention to produce sentences that describe C# code snippets and SQL queries from StackOverflow. Torch over C#/SQL
-* [Probabilistic API Miner](https://github.com/mast-group/api-mining) - PAM is a near parameter-free probabilistic algorithm for mining the most interesting API patterns from a list of API call sequences. 
-* [Interesting Sequence Miner](https://github.com/mast-group/sequence-mining) - ISM is a novel algorithm that mines the most interesting sequences under a probabilistic model. It is able to efficiently infer interesting sequences directly from the database. 
-* [TASSAL](https://github.com/mast-group/tassal) - TASSAL is a tool for the automatic summarization of source code using autofolding. Autofolding automatically creates a summary of a source code file by folding non-essential code and comment blocks.
+* [Probabilistic API Miner](https://github.com/mast-group/api-mining) - Near parameter-free probabilistic algorithm for mining the most interesting API patterns from a list of API call sequences. 
+* [Interesting Sequence Miner](https://github.com/mast-group/sequence-mining) - Novel algorithm that mines the most interesting sequences under a probabilistic model. It is able to efficiently infer interesting sequences directly from the database. 
+* [TASSAL](https://github.com/mast-group/tassal) - Tool for the automatic summarization of source code using autofolding. Autofolding automatically creates a summary of a source code file by folding non-essential code and comment blocks.
 * [JNice2Predict](http://www.nice2predict.org/) - Efficient and scalable open-source framework for structured prediction, enabling one to build new statistical engines more quickly.
 
 <a name="software-utilities"></a>
 #### Utilities
-* [go-git](https://github.com/src-d/go-git) - A highly extensible Git implementation in pure Go which is friendly to data mining.
+* [go-git](https://github.com/src-d/go-git) - Highly extensible Git implementation in pure Go which is friendly to data mining.
 * [hercules](https://github.com/src-d/hercules) - Git repository mining framework with batteries on top of go-git.
-* [bblfsh](https://github.com/bblfsh) - A self-hosted server for source code parsing.
-* [engine](https://github.com/src-d/engine) - A scalable and distributed data retrieval pipeline for source code.
+* [bblfsh](https://github.com/bblfsh) - Self-hosted server for source code parsing.
+* [engine](https://github.com/src-d/engine) - Scalable and distributed data retrieval pipeline for source code.
 * [minhashcuda](https://github.com/src-d/minhashcuda) - Weighted MinHash implementation on CUDA to efficiently find duplicates.
 * [kmcuda](https://github.com/src-d/kmcuda) - k-means on CUDA to cluster and to search for nearest neighbors in dense space.
 * [wmd-relax](https://github.com/src-d/wmd-relax) - Python package which finds nearest neighbors at Word Mover's Distance.