pomagma 0.2.4

An inference engine for extensional lambda-calculus

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# Pomagma

Pomagma is an inference engine for
[extensional untyped λ-calculus](/doc/philosophy.md).
Pomagma is useful for:

* simplifying code fragments expressed in pure λ-join calculus
* validating entire codebases of λ-terms and inequalities
* testing and validating systems of inequalities
* solving systems of inequalities

Pomagma has client libraries in python and node.js, and powers the
[Puddle](https://github.com/fritzo/puddle) reactive coding environment.
The correctness of Pomagma's theory is being verified in the
[Hstar project](https://github.com/fritzo/hstar).

## Documentation

* [Philosophy](/doc/philosophy.md)
* [Using a client library](/doc/client.md)
* [Administering a server](/doc/server.md)

## Installing

The server targets Ubuntu 14.04 and 12.04, and installs in a python virtualenv.

git clone https://github.com/fritzo/pomagma
cd pomagma
. install.sh
make small-test # takes ~5 CPU minutes
make test # takes ~1 CPU hour

Client libraries support Python 2.7 and Node.js.

pip install pomagma
npm install pomagma

## Quick Start

Start a local analysis server with the tiny default atlas

python -m pomagma analyze # starts server, Ctrl-C to quit

Then in another terminal, start an interactive client session

python -m pomagma connect # starts client session

Alternatively, connect using the Python client library

python
from pomagma import analyst
with analyst.connect() as db:
print db.simplify(["APP I I"]) # prints [I]
print db.validate(["I"]) # prints [{"is_bot": False, "is_top": False}]

or the Node.js client library

nodejs
var analyst = require("pomagma").analyst;
var db = analyst.connect();
console.log(db.simplify(["APP I I"])); // prints [I]
console.log(db.validate(["I"])); // prints [{"is_bot": false, "is_top": false}]
db.close();

## Get an Atlas to power an analysis server

Pomagma reasons about large programs by approximately locating code fragments
in an **atlas** of 10³-10⁵ basic programs.
The more basic programs in an atlas,
the more accurate pomagma's analysis will be.
Pomagma ships with a tiny default atlas of ~2000 basic programs.

To get a large prebuild atlas, put your AWS credentials in the environment and

python -m pomagma pull # downloads atlas from S3 bucket

To start building a custom atlas from scratch

python -m pomagma make max_size=10000 # kill and restart at any time

Pomagma is parallelized and needs lots of memory to build a large atlas.

| Atlas Size | Compute Time | Memory Space | Storage Space |
|---------------|--------------|--------------|----------------------|
| 1 000 atoms | ~1 CPU hour | ~10MB | ~1MB uncompressed |
| 10 000 atoms | ~1 CPU week | ~1GB | ~100MB uncompressed |
| 100 000 atoms | ~5 CPU years | ~100GB | ~10GB uncompressed |

## License

Copyright 2005-2015 Fritz Obermeyer.<br/>
All code is licensed under the [Apache 2.0 License](/LICENSE)
unless otherwise noted.

Code in [/src/protobuf](/src/protobuf)
is Copyright 2014 Salesforce.com, Inc.<br/>
and released under the [Revised BSD License](/src/protobuf/LICENSE).