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Projeto da competição do GHC. Mais informações: https://garoa.net.br/wiki/GCC_2014
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README.rst

Turing Machine online in Flask

A simple Turing machine simulator using Flask (Python).

About the Turing Machine

The Turing a-machine (automatic machine) was defined by Alan M. Turing in his paper "On computable numbers, with an application to the Entscheidungsproblem" (1936):

http://classes.soe.ucsc.edu/cmps210/Winter11/Papers/turing-1936.pdf

There are several useful books and other sources of information available about that machine, for example the Wikipedia has a several references about it:

http://en.wikipedia.org/wiki/Turing_machine

There are some diferences with the way Turing organized the ideas and his terminology with the one used by some contemporary writers. The names and expressions within this project tried to be as near as possible to the ones used in his original paper. That happened as well with the way the machine rules/instructions are written as input for the system, trying to remember the ordering and contents written by Turing himself in that writing. As an example:

b None ->  P0  R  c
c None ->    R    e
e None ->  P1  R  f
f None ->    R    b

This is the first example given by Turing in his paper, written in the same order he wrote:

m-configuration ; scanned symbol -> behaviour ; final m-configuration

Where the m-configuration is the name he gives for the internal "state of mind" of the computer, and the behaviour is a list of tasks to be performed in order. Later he "normalizes" it into 3 (three) kinds of rules that entails every other rule, however in this implementation here, the syntax allows more than such minimalism. For example, his second example, which generates the same tape as the result, also works in this system:

b None ->   P0   b
     0 -> R R P1 b
     1 -> R R P0 b

For more information about the machine, the reader should find it on the links above.

Testing

The tests were done on the project core, for the Turing Machine model implemented in the backend, in a TDD-like fashion.

The tests were done with py.test, a requirement for running the tests by yourself. The file test_turing.py is a callable to run with py.test, but calling py.test directly from the root directory of this project works as well:

~/GCodeCompetition $ py.test
======================== test session starts =========================
platform linux -- Python 3.3.0 -- pytest-2.4.0.dev2
plugins: cov
collected 39 items

test_turing.py .......................................

===================== 39 passed in 0.08 seconds ======================

Running with code coverage statistics in Python 2.7.3:

~/GCodeCompetition $ py.test-2.7 --cov turing
======================== test session starts =========================
platform linux2 -- Python 2.7.3 -- pytest-2.4.0.dev2
plugins: timeout, xdist, cov
collected 39 items

test_turing.py .......................................
---------- coverage: platform linux2, python 2.7.3-final-0 -----------
Name     Stmts   Miss  Cover
----------------------------
turing     130     10    92%

===================== 39 passed in 0.11 seconds ======================

As shown above, the core was tested under Python 3.3.0 and 2.7.3, working on both successfully with the same code. The tests includes the two examples said in the "About the Turing Machine" section, although these aren't for finding something like a "final" m-configuration (indeed, they're endless examples).

Installing

This is a common Flask project, needing the flask itself for practical use. Tested with Flask 0.9 (Python 2.7.3) and Flask 0.10.1 (Python 3.3.0). It can be installed in a virtual environment easily after cloning the project from GitHub:

$ virtualenv --distribute --python=python3.3 venv
$ source venv/bin/activate
$ pip install flask
$ python main.py

This is mainly for debugging and evaluation. As a flask project, for deploying you'll need an IaaS/PaaS that allows WSGI servers (better yet if there's everything already done for Flask).

As said before, py.test (pip install pytest) should be installed for running the tests. For the code coverage shown above, it also needs the pytest-cov package.

About this project

Originally made for GCC (Garoa Code Competition), mainly as a way to allow Turing Machine Coding Dojos to happen in the near future, and also to help people understand what the Turing Machine is, perhaps motivating them to read about the subject, including the original/historical papers like the one Turing wrote in 1936. More information about the GCC can be found in this link:

https://garoa.net.br/wiki/GCC_2014

static/GCC-logo.png

Hopefully there are enough comments about the functionalities of this project in the code to help its comprehension for new developers for this project.

How to use

The Turing Machine is a machine with rules/instructions, such as:

q1 0 -> P1 R q2

That says that a machine in the m-configuration q1 and scanning the symbol 0 should [P]rint the symbol 1, move to the [R]ight and change to the m-configuration q2 The identification is rather arbitrary, the main symbols are the -> that splits the "before" (configuration) and "after" (what to be done) timings of the rule, the P (print), E (erase), R (right) and L (left), which tells us about the way the tasks are performed, keeping the way Turing used to express them.

Another words are the None and the Not, both used by Turing, alowing rules like:

q1 Not 3 -> PNone R q2

Although E is probably way cleaner than PNone (is it?). The capital None is the blank symbol itself, and Not works as a negation of the symbol that follows. Also, a set of symbols for the scanned symbol possibilities might be used, like [0 1] or Not [1 2], using square brackets. That obviously don't change the power of the Turing Machine, just groups some rules together to make a perceived smaller set of instructions to the programmer.

The absence of a symbol means that "any" symbol is valid. Both this "any" behavior and the Not have lower priority in the choice of rules when there's some indeterminancy. The other criteria is the rule ordering, which also gives us the first m-configuration (which is the m-configuration of the first rule).

Lines starting with at least one whitespace might help as they're considered something that continues the last line. Like:

q1   2   -> q2
   Not 3 -> R q1

The second rule doesn't have the q1, but as it starts after a whitespace, the last m-configuration is implicit. The same happens can be organized as a separated line for grouping:

q1
   0 -> L q3
   1 -> R q4

And for lines that breaks after the -> symbol, the line below is seen as part of the line above it, i.e.:

q1 0 -> L
        P0 R
        P1 R
        P0 L q4

Is the same to a single line:

q1 0 -> L P0 R P1 R P0 L q4

Other details can be seen in the code. Most of these were done to replicate the "syntax" Turing used and to try to keep the act of programming "for humans" in some (perhaps lazy) sense.


License is MIT. See COPYING.txt for more details.

By Danilo J. S. Bellini and Nicolas França

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