OPiE

Object Programming Environment

Introduction

This writing intends to cover advanced programming concepts that some would consider an extension of the operating system.  However, I am including these concepts in a book on programming in order to establish these principles as universally applicable in a computer programming capacity.  A more technical description of this paradigm may include hardware-specific features like a description of automata-based data structures and their representation in computer memory.  A more high-level approach is presumed in this literature for the sake of limiting the scope of this literature to advanced programming techniques.  The paradigm of encapsulating coding hiding the complexity.  The premise is analogically the equivalent of “driving” a car but not necessarily knowing how the engine works.  These techniques include temporal scheduling, file system operations or object persistence through database storage of serialized objects, user agency and authentication protocols, & networking protocols.  The main objective of this software is to provide a “sandbox” programming environment that encapsulates and offers wrapper functionality to many features traditionally provided by the operating system, primarily, the UNIX-based system.  The “automata” paradigm of this implementation categorizes it as artificial intelligence while the novel, “nudge” intuition of combining authentication protocols, object serialization, temporal logic, & automata invokes a new paradigm for the power of UNIX command-line based systems.  These techniques consist of research performed at the Knowledge Management Lab at Florida International University in Miami, FL, USA and represent advanced programming concepts not instructed in intermediate or advanced college programming courses and is not intended as a deliberation of a completely disseminated functional system, merely a description of the concepts presented.  The research was undertaken under the direction of NASA computer engineer Chris Knight of Ames Research Center.  Much of this content is taken directly from the development source code repository at the jcrow github account at:

http://www.github.com/jcrow

Namely, the OpiE, corevet, objix, and mpy source code repositories.

This literature assumes a working knowledge of programming using examples in python.  Also, some materials are included in the appendix for basic UNIX commands and how to implement and use a UNIX OS host on google cloud.

Table of Contents

Object-Orientation

Serialization & Persistence

File I/O

User Agency & Authentication

Temporal Logic

Network Polling

References

User Agency & Authentication

A big issue in modern computing is safeguarding access to data.  There are several aspects to security that must be address in modern information systems.  Security must be deployed for both internal users of a system and external threats.  Authentication defines a paradigm by which access to sensitive data can be secured.

ACL & ACE

The ACL (Access Control List) & ACE (Access Control Entry) authentication protocol is a powerful tool in addressing both internal & external security needs.  Basically, the ACL defines a list of ACE’s, each of which defines a set of unix-like permissions on a file or database field which include:

• Read
• Write
• Execute
• Delete

The ACE defines a user or list of users that have a certain type of access to a defined data field and the ACL is a list of ACE entries.  Authentication in this case utilizes a username & password mechanism and data fields available in an information system are accessible subject to this protocol.

{graphic}

{code}

import crypt, getpass, pwd

def login(self, p):
   username = raw_input('Python login:')
   cryptedpasswd = pwd.getpwnam(username)[1]
   if cryptedpasswd:

if cryptedpasswd == 'x' or cryptedpasswd == '*':
            raise NotImplementedError(
    "Sorry, currently no support for shadow passwords")
            cleartext = getpass.getpass()

return crypt.crypt(cleartext, cryptedpasswd) == cryptedpasswd

else:
       return 1

crypt authenticates by cryptographically converting login password in an impossible to reverse algorithm and matches this encrypted string against the encrypted string in the db.

Here are some example classes implementing the ACL/ACE authentication protocol:

class acl:

    __objects = {}

    def get_ace(self, objid):

        return __objects[objid]

    def set_ace(self, objid, permissions=[]):

        self.__objects[objid] = permissions

And the ACE:

Object Persistence & Serialization

In more advanced software & operating environments, serialized objects are stored as entries in a database, however, for the purposes of this reading, I am using file i/o operations and strings.  Later on I will show an example that combines the concepts of object serialization, user authentication through ACL’s, temporal logic, & object persistence.

import pickle

class Obj:

        id = -1

        attributes = {}

        def get_id(self):

                return id

        def set_id(self, n):

                Id = n

        def get_attr(self, key):

                return attributes[key]

        def set_attr(self, key, val):

                attributes[key] = val

        def get_all_attr(self):

                return attributes

        def serialize(self):

                return pickle.dumps(self)

r = Obj()

r.set_id = 1

r.set_attr(‘data’, 123)

o = open(‘objfile.dat’, ‘w’)

o.write (r.serialize())

o.close()

Here is the same code with several objects instantiated and stored in a file:

import pickle

class Obj:

        id = -1

        attributes = {}

        def get_id(self):

                return id

        def set_id(self, n):

                Id = n

        def get_attr(self, key):

                return attributes[key]

        def set_attr(self, key, val):

                attributes[key] = val

        def get_all_attr(self):

                return attributes

        def serialize(self):

                return pickle.dumps(self)

r = Obj()

r.set_id = 1

r.set_attr(‘data’, 123)

r2 = Obj()

r2.set_id = 2

r.set_attr(‘data’, 456)

r3 = Obj()

r3.set_id = 3

r3.set_attr(‘data’, 789(

filedata = ‘’

filedata = r.serialize()+’\n’+r2.serialize()+’\n’+r3.serialize()

o = open(‘objfile2.dat’, ‘w’)

o.write (filedata)

o.close()

A feature of this environment that is useful for data integrity is the execution of function-based inheritance where an update to a parent object automatically loops through and populates each of the new fields in child objects with the added property or object method.

File I/O

Throughout this book, I am using file i/o operations instead of database to avoid including a lot of SQL statements.  The necessary file i/o commands are available below.

For reading from a file:

o = open(‘file1.dat’)

filedata = o.read()

print filedata

o.close()

For writing to a file:

O = open(‘file2.dat’, ‘w’)

filedata2 = ‘somedata’

o.write(filedata2)

o.close()

Temporal Logic & Event Management

This paradigm attempts to include time based logical control over a programming code sequence that would be typically considered as part of the operating system, with cron in unix for example.  However, I am including this concept in a book on programming to establish this paradigm as an essential conceptual feature in programming in a universal sense.

import time

def func(arg):

        print arg

a = time.time()+100

while 1:

        If time.time()<a:

                time.sleep(30)

        else:

                func(‘hello world!’)

                break

Another interesting variation is to perennially repeat this “timed” function call by adding 60 seconds to the timing feature every time the function is called:

import time

def func(arg):

        print arg

a = time.time()+100

while 1:

        If time.time()<a:

                time.sleep(30)

        else:

                func(‘hello world!’)

                a = a + 60

#break

Also, consider a list of functions each with a time key to be executed temporally:

import time

def func(arg):

        print arg

def func2():

        print ‘hello world2!’

def func3():

        Print ‘hello world3!’

a = time.time()+ 100

b = time.time() + 50

c = time.time() + 125

e = {a: func, b: func2, c: func3}

while 1:

        for x in e.keys()

        if time.time()<x:

                        continue

                else:

                        e[x]()

                        e.pop(x, 0)

        if e:

        time.sleep(30)

        else:

                break

Also, using the same code, you can manipulate the event dictionary data structure to execute the listed function at timed intervals:

import time

def func(arg):

        print arg

def func2():

        print ‘hello world2!’

def func3():

        Print ‘hello world3!’

a = time.time()+ 100

b = time.time() + 50

c = time.time() + 125

e = {a: [func, 45], b: [func2, 60], c: [func3, 20]}

while 1:

        for x in e.keys()

        if time.time()<x:

                        continue

                else:

                        e[x]()

                        e[x+e[x][1]] = [e[x][0], e[x][1]]

                        e.pop(x, 0)

time.sleep(30)

Interoperation between temporal logic and a finite-state machine becomes interesting as time-based execution of functions are arranged along a fsm automata

A critical feature of this temporal logic manager is the premise of an “appointment setter” on a dynamic basis where updates in the data store can generate timed release and response with user interaction through the state machine functionality described below.  An interesting add-on based on this concept is a time-based logistics manager that arranges meetings or materials shipment through a cost and temporal API such as SABRE or transit.google.com indicating travel logistics or time-based arrangements resulting in reduced turn-around times.  The management of logistics may seem trivial for a small group of people but consider an organization like NASA with thousands of employees.  Consider a module that tracks and manages logistics.  Notification of changes in flight cost or even drilling down to the maintenance of a vehicle could be invaluable sources of managerial decision-making.

(TODO: edit code so OO db is used, inherit generic Obj class to add state machine properties as in objix, mpy code in cvs repository)

class StateMachine:
   def __init__(self):
       self.handlers = {}
       self.startState = None
       self.endStates = []

   def add_state(self, name, handler, end_state=0):
       name = name.upper()
       self.handlers[name] = handler
       if end_state:
           self.endStates.append(name)

   def set_start(self, name):
       self.startState = name.upper()

   def run(self, cargo):
       try:
           handler = self.handlers[self.startState]
       except:
           raise InitializationError("must call .set_start() before .run()")
       if not self.endStates:
           raise  InitializationError("at least one state must be an end_state")
   
       while True:
           (newState, cargo) = handler(cargo)
           if newState.upper() in self.endStates:
               print("reached ", newState)
               break
           else:
               handler = self.handlers[newState.upper()]

while a full-fledged state machine with transitions and temporal logic may appear like this:

def start_transitions(txt):
   splitted_txt = txt.split(None,1)
   word, txt = splitted_txt if len(splitted_txt) > 1 else (txt,"")
   if word == "Python":
       newState = "Python_state"
   else:
       newState = "error_state"
   return (newState, txt)

def python_state_transitions(txt):
   splitted_txt = txt.split(None,1)
   word, txt = splitted_txt if len(splitted_txt) > 1 else (txt,"")
   if word == "is":
       newState = "is_state"
   else:
       newState = "error_state"
   return (newState, txt)

def is_state_transitions(txt):
   splitted_txt = txt.split(None,1)
   word, txt = splitted_txt if len(splitted_txt) > 1 else (txt,"")
   if word == "not":
       newState = "not_state"
   elif word in positive_adjectives:
       newState = "pos_state"
   elif word in negative_adjectives:
       newState = "neg_state"
   else:
       newState = "error_state"
   return (newState, txt)

def not_state_transitions(txt):
   splitted_txt = txt.split(None,1)
   word, txt = splitted_txt if len(splitted_txt) > 1 else (txt,"")
   if word in positive_adjectives:
       newState = "neg_state"
   elif word in negative_adjectives:
       newState = "pos_state"
   else:
       newState = "error_state"
   return (newState, txt)

def neg_state(txt):
   print("Hallo")
   return ("neg_state", "")

if __name__== "__main__":
   m = StateMachine()
   m.add_state("Start", start_transitions)
   m.add_state("Python_state", python_state_transitions)
   m.add_state("is_state", is_state_transitions)
   m.add_state("not_state", not_state_transitions)
   m.add_state("neg_state", None, end_state=1)
   m.add_state("pos_state", None, end_state=1)
   m.add_state("error_state", None, end_state=1)
   m.set_start("Start")
   m.run("Python is great")
   m.run("Python is difficult")
   m.run("Perl is ugly")

Using the example of a decision tree type of finite state machine with the application of project development would appear like this:

{TODO: create statemachine for project diagram: https://www.smartdraw.com/decision-tree/}

TEMPORAL LOGIC, SWITCH OPERATORS, & LOOPS

An interesting approach to encapsulate automata formulas with is by using switch operator functions as loops with a temporal aspect.  For example, the previous mention of temporal logic and timing the execution of functions can be used in a process design by re-executing the value of a variable, a sequence repeatable periodically, infinitely or with a finite number of processing.

(Decision Tree)

m = StateMachine()

m

Interestingly, many nodes on this tree would require authentication protocols to other files such as accounting ledgers to determine the budget and project scheduling to decide on timescale.  Also, the functions that correspond to transitions between states in this diagram could conveniently be represented visually from an automata model editor populating drop-down lists.  An issue with this approach is managing the namespace for these system- or user-defined functions.  The likely position of the namespace in memory would be the cron thread or server process loading the python objects.  With C++ this position can be detected by pointers however, to retrieve the namespace position in python, for example:

b = obj.__self__

Another interesting application of fsm automata with regards to workflow-based automation of system entry into mainframe applications makes use of the py3270 library offering terminal emulator functions.  It is available at:

from py3270 import EmulatorBase

class Emulator(EmulatorBase):
   x3270_executable = '/fake/x3270'
   s3270_executable = '/fake/s3270'

# use x3270 so you can see what is going on
em = Emulator(visible=True)

# or not (uses s3270)
em = Emulator()

em.connect('3270host.example.com')
em.fill_field(17, 23, 'mylogin', 8)
em.fill_field(18, 23, 'mypass', 8)
em.send_enter()

# if your host unlocks the keyboard before truly being ready you can use:
em.wait_for_field()

# maybe look for a status message
if not em.string_found(1, 2, 'login succesful'):
   abort()

# do something useful

# disconnect from host and kill subprocess
em.terminate()

LIBRARY OF CONGRESS EXAMPLE

searching the library of congress mainframe for Harry Potter in Hebrew:

#!/usr/bin/env python

# encoding: utf-8

from PyZ3950 import zoom

from PyZ3950 import zmarc

import sys

reload(sys)

sys.setdefaultencoding('utf8')

conn = zoom.Connection('z3950.loc.gov', 7090)

conn.databaseName = 'VOYAGER'

query = zoom.Query('CCL', 'ti="HARRY POTTER"')

res = conn.search(query)

print "%d hits:" % len(res)

for r in res[:1]:

print unicode( r.data )

https://pypi.python.org/pypi/py3270/0.1.4

Also interesting prospective use is the pywinauto library which can emulate windows application entry & control.  It is available at:

a) create an instance of the Application class first and then call start() on it.

>>> from pywinauto import Application

>>> app = Application()

>>> app.start('notepad.exe')

<pywinauto.application.Application object at 0x022991B0>

>>> app.UntitledNotepad.MenuItem("File -> Exit").Select()

b) call the Application.Start() class method. (starts with uppercase 'S')

>>> app = Application.Start('Notepad')

>>> app.UntitledNotepad.MenuItem("File -> Exit").Select()

http://stackoverflow.com/questions/5452830/error-using-pywinauto

https://sourceforge.net/projects/pywinauto/

:

EXECUTING UNIX COMMANDS ON THE WEB

import subprocess

data = cgi.FieldStorage()

if data.has_key('cmd'):

        mycmd = data['mycmd'].value

p = subprocess.Popen([, '-a'], stdout=subprocess.PIPE, stderr=subprocess.PIPE)

out, err = p.communicate()

print out

data = cgi.FieldStorage() if data.has_key('ID'): myID = data['myID'].value if testme(ID): #checks if ID exists in dictionary printmessages(myID) addmessage(myID) elif data.has_key('newitem'): newmitem = data['newitem'].value insertmessage(myID, newitem)

Running as a command wrapper for cron or other time-based servers, a bash script can be executed based on timed inputs from an automata FSM scheme

Network Polling

In this code, I am attempting to poll a network of online english-speaking newspapers via http, check the front pages for the appearance of the term “GOLD’, and tally the results.  The same can be done with a list of objects, a set of urls, or a list of web service references.

import urllib2

import string

import time

import mysql.connector

import sys

reload(sys)

sys.setdefaultencoding('utf8')

#file i/o operations

f = open('f3.txt')

f = f.read()

f = f.split('\n')

G = 0

for x in f:

        try:

                p = urllib2.urlopen(x, timeout=30)

                p = p.read()

                p = string.upper(p)

                for y in f2:

                        if string.find(p, ‘GOLD’)>-1:

                                G = G + 1

                                print x+'\t'+y

                        print x

        except:

                continue

APPENDIX

USING A GOOGLE CLOUD HOST

https://cloud.google.com/compute/docs/quickstarts

BASIC UNIX COMMANDS

Files

• ls --- lists your files
• ls -l --- lists your files in 'long format', which contains lots of useful information, e.g. the exact size of the file, who owns the file and who has the right to look at it, and when it was last modified.
• ls -a --- lists all files, including the ones whose filenames begin in a dot, which you do not always want to see.
• There are many more options, for example to list files by size, by date, recursively etc.
• more filename --- shows the first part of a file, just as much as will fit on one screen. Just hit the space bar to see more or q to quit. You can use /pattern to search for a pattern.
• emacs filename --- is an editor that lets you create and edit a file. See the emacs page.
• mv filename1 filename2 --- moves a file (i.e. gives it a different name, or moves it into a different directory (see below)
• cp filename1 filename2 --- copies a file
• rm filename --- removes a file. It is wise to use the option rm -i, which will ask you for confirmation before actually deleting anything. You can make this your default by making an alias in your .cshrc file.
• diff filename1 filename2 --- compares files, and shows where they differ
• wc filename --- tells you how many lines, words, and characters there are in a file
• chmod options filename --- lets you change the read, write, and execute permissions on your files. The default is that only you can look at them and change them, but you may sometimes want to change these permissions. For example, chmod o+r filename will make the file readable for everyone, and chmod o-r filename will make it unreadable for others again. Note that for someone to be able to actually look at the file the directories it is in need to be at least executable. See help protection for more details.
• File Compression

• gzip filename --- compresses files, so that they take up much less space. Usually text files compress to about half their original size, but it depends very much on the size of the file and the nature of the contents. There are other tools for this purpose, too (e.g. compress), but gzip usually gives the highest compression rate. Gzip produces files with the ending '.gz' appended to the original filename.
• gunzip filename --- uncompresses files compressed by gzip.
• gzcat filename --- lets you look at a gzipped file without actually having to gunzip it (same as gunzip -c). You can even print it directly, using gzcat filename | lpr

• printing

• lpr filename --- print. Use the -P option to specify the printer name if you want to use a printer other than your default printer. For example, if you want to print double-sided, use 'lpr -Pvalkyr-d', or if you're at CSLI, you may want to use 'lpr -Pcord115-d'. See 'help printers' for more information about printers and their locations.
• lpq --- check out the printer queue, e.g. to get the number needed for removal, or to see how many other files will be printed before yours will come out
• lprm jobnumber --- remove something from the printer queue. You can find the job number by using lpq. Theoretically you also have to specify a printer name, but this isn't necessary as long as you use your default printer in the department.
• genscript --- converts plain text files into postscript for printing, and gives you some options for formatting. Consider making an alias like alias ecop 'genscript -2 -r \!* | lpr -h -Pvalkyr' to print two pages on one piece of paper.
• dvips filename --- print .dvi files (i.e. files produced by LaTeX). You can use dviselect to print only selected pages. See the LaTeX page for more information about how to save paper when printing drafts.

Directories

Directories, like folders on a Macintosh, are used to group files together in a hierarchical structure.

• mkdir dirname --- make a new directory
• cd dirname --- change directory. You basically 'go' to another directory, and you will see the files in that directory when you do 'ls'. You always start out in your 'home directory', and you can get back there by typing 'cd' without arguments. 'cd ..' will get you one level up from your current position. You don't have to walk along step by step - you can make big leaps or avoid walking around by specifying pathnames.
• pwd --- tells you where you currently are.

Finding things

• ff --- find files anywhere on the system. This can be extremely useful if you've forgotten in which directory you put a file, but do remember the name. In fact, if you use ff -p you don't even need the full name, just the beginning. This can also be useful for finding other things on the system, e.g. documentation.
• grep string filename(s) --- looks for the string in the files. This can be useful a lot of purposes, e.g. finding the right file among many, figuring out which is the right version of something, and even doing serious corpus work. grep comes in several varieties (grep, egrep, and fgrep) and has a lot of very flexible options. Check out the man pages if this sounds good to you.

About other people

• w --- tells you who's logged in, and what they're doing. Especially useful: the 'idle' part. This allows you to see whether they're actually sitting there typing away at their keyboards right at the moment.
• who --- tells you who's logged on, and where they're coming from. Useful if you're looking for someone who's actually physically in the same building as you, or in some other particular location.
• finger username --- gives you lots of information about that user, e.g. when they last read their mail and whether they're logged in. Often people put other practical information, such as phone numbers and addresses, in a file called .plan. This information is also displayed by 'finger'.
• last -1 username --- tells you when the user last logged on and off and from where. Without any options, last will give you a list of everyone's logins.
• talk username --- lets you have a (typed) conversation with another user
• write username --- lets you exchange one-line messages with another user
• elm --- lets you send e-mail messages to people around the world (and, of course, read them). It's not the only mailer you can use, but the one we recommend. See the elm page, and find out about the departmental mailing lists (which you can also find in /user/linguistics/helpfile).

About your (electronic) self

• whoami --- returns your username. Sounds useless, but isn't. You may need to find out who it is who forgot to log out somewhere, and make sure *you* have logged out.
• finger & .plan files
• of course you can finger yourself, too. That can be useful e.g. as a quick check whether you got new mail. Try to create a useful .plan file soon. Look at other people's .plan files for ideas. The file needs to be readable for everyone in order to be visible through 'finger'. Do 'chmod a+r .plan' if necessary. You should realize that this information is accessible from anywhere in the world, not just to other people on turing.
• passwd --- lets you change your password, which you should do regularly (at least once a year). See the LRB guide and/or look at help password.
• ps -u yourusername --- lists your processes. Contains lots of information about them, including the process ID, which you need if you have to kill a process. Normally, when you have been kicked out of a dialin session or have otherwise managed to get yourself disconnected abruptly, this list will contain the processes you need to kill. Those may include the shell (tcsh or whatever you're using), and anything you were running, for example emacs or elm. Be careful not to kill your current shell - the one with the number closer to the one of the ps command you're currently running. But if it happens, don't panic. Just try again :) If you're using an X-display you may have to kill some X processes before you can start them again. These will show only when you use ps -efl, because they're root processes.
• kill PID --- kills (ends) the processes with the ID you gave. This works only for your own processes, of course. Get the ID by using ps. If the process doesn't 'die' properly, use the option -9. But attempt without that option first, because it doesn't give the process a chance to finish possibly important business before dying. You may need to kill processes for example if your modem connection was interrupted and you didn't get logged out properly, which sometimes happens.
• quota -v --- show what your disk quota is (i.e. how much space you have to store files), how much you're actually using, and in case you've exceeded your quota (which you'll be given an automatic warning about by the system) how much time you have left to sort them out (by deleting or gzipping some, or moving them to your own computer).
• du filename --- shows the disk usage of the files and directories in filename (without argument the current directory is used). du -s gives only a total.
• last yourusername --- lists your last logins. Can be a useful memory aid for when you were where, how long you've been working for, and keeping track of your phonebill if you're making a non-local phonecall for dialling in.

Connecting to the outside world

• nn --- allows you to read news. It will first let you read the news local to turing, and then the remote news. If you want to read only the local or remote news, you can use nnl or nnr, respectively. To learn more about nn type nn, then \tty{:man}, then \tty{=.*}, then \tty{Z}, then hit the space bar to step through the manual. Or look at the man page. Or check out the hypertext nn FAQ - probably the easiest and most fun way to go.
• rlogin hostname --- lets you connect to a remote host
• telnet hostname --- also lets you connect to a remote host. Use rlogin whenever possible.
• ftp hostname --- lets you download files from a remote host which is set up as an ftp-server. This is a common method for exchanging academic papers and drafts. If you need to make a paper of yours available in this way, you can (temporarily) put a copy in /user/ftp/pub/TMP. For more permanent solutions, ask Emma. The most important commands within ftp are get for getting files from the remote machine, and put for putting them there (mget and mput let you specify more than one file at once). Sounds straightforward, but be sure not to confuse the two, especially when your physical location doesn't correspond to the direction of the ftp connection you're making. ftp just overwrites files with the same filename. If you're transferring anything other than ASCII text, use binary mode.
• lynx --- lets you browse the web from an ordinary terminal. Of course you can see only the text, not the pictures. You can type any URL as an argument to the G command. When you're doing this from any Stanford host you can leave out the .stanford.edu part of the URL when connecting to Stanford URLs. Type H at any time to learn more about lynx, and Q to exit.

Miscellaneous tools

• webster word --- looks up the word in an electronic version of Webster's dictionary and returns the definition(s)
• date --- shows the current date and time.
• cal --- shows a calendar of the current month. Use e.g., 'cal 10 1995' to get that for October 95, or 'cal 1995' to get the whole year.

You can find out more about these commands by looking up their manpages:

man commandname --- shows you the manual page for the command (UNIX)

UNIX TEXT EDITORS

• nano
• vi
• pico

STARTING PYTHON

>>python

RUNNING PYTHON SCRIPT

>>python filename.py

or:

>>import filename

STARTING UNIX EDITORS

>>nano filename

INSTALLING LAMP ON GOOGLE HOST

https://cloud.google.com/compute/docs/tutorials/setting-up-lamp

SQL

http://www.w3schools.com/sql/

FSM: finite state machine automata info

http://www.python-course.eu/finite_state_machine.php

{TODO: mysql implementation and installation/LAMP, gcloud ftp, .csv}

REFERENCES

Becerra, I., McCarthy, K., & Rodriguez, J. (2001). An Infrastructure for Managing Knowledge Using Intelligent Workflow. Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference, 275-279.

Becerra, I., & Rodriguez, J. (2001). Web Data Mining Techniques for Expertise-Locator Knowledge Management Systems. Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference, 280-285.

Rodriguez, J. (n.d.). jcrow/corevet. Retrieved April 28, 2016, from https://github.com/jcrow/corevet

Rodriguez, J. (n.d.). jcrow/objix. Retrieved April 28, 2016, from https://github.com/jcrow/objix

Rodriguez, J. (n.d.). jcrow/mpy. Retrieved April 28, 2016, from https://github.com/jcrow/mpy

Basic UNIX commands. (n.d.). Retrieved June 23, 2016, from http://mally.stanford.edu/~sr/computing/basic-unix.html

Decision Tree. (n.d.). Retrieved July 10, 2016, from https://www.smartdraw.com/decision-tree/