ROBERT RYAN COX
Pilots at Oak Vw, Round Rock, TX

License number
Texas A5177970
Issued Date
Apr 2014
Expiration Date
Apr 2017
Category
Airmen
Type
Authorized Aircraft Instructor
Address
Address
9 Oak Vw, Round Rock, TX 78664

Personal information

See more information about ROBERT RYAN COX at radaris.com
Name
Address
Phone
Robert Cox, age 60
5105 Peach Tree Ln, Sachse, TX 75048
(972) 412-3793
Robert Cox, age 68
5100 Teinert Rd, Giddings, TX 78942
Robert Cox
5032 San Marcus Dr, Mesquite, TX 75150
Robert Cox, age 71
508 Park St, Gilmer, TX 75644
(281) 773-0353
Robert Cox
514 Sulphur St, Houston, TX 77034
(713) 502-6701

Professional information

See more information about ROBERT RYAN COX at trustoria.com
Robert Cox Photo 1
Method And Apparatus For Training An Automated Software Test

Method And Apparatus For Training An Automated Software Test

US Patent:
6349393, Feb 19, 2002
Filed:
Jan 29, 1999
Appl. No.:
09/240923
Inventors:
Robert Charles Cox - Round Rock TX
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 1100
US Classification:
714 38, 714 25, 703 22, 717 1
Abstract:
An automated software test is provided which includes a functional model of a system to be tested. The automated software test is utilized to operate a system under test in accordance with specified facts, goals and rules. Quasi-random actions are taken within the system in accordance with specified rules and facts until a defined goal has been accomplished. Training the automated software test is accomplished by specifying a particular goal, i. e. identifying a particularly known defect, and thereafter running the test in a quasi-random fashion until the particular goal has been achieved. The number and nature of actions required to achieve that goal are logged and the process is then repeated until the shortest path required to achieve that goal has been determined. The log of actions which eventually reach a particularly defect may also be utilized a probable cause tree structure for future analysis.


Robert Cox Photo 2
System And Method For Automated Testing Of Software Systems Utilizing Statistical Models

System And Method For Automated Testing Of Software Systems Utilizing Statistical Models

US Patent:
6460147, Oct 1, 2002
Filed:
Dec 10, 1998
Appl. No.:
09/210209
Inventors:
Robert Charles Cox - Round Rock TX
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
H04L 122
US Classification:
714 38, 714 25, 703 22, 707 1
Abstract:
The architecture of the Smart Test is described. Instead of writing a script, the Tester designs a functional model of the system to be tested, such as an application. For example, the Tester would model the functions of the system to be tested, such as a main window, a menu bar, drop-down menus, specialized windows etc. The more complete the model, the better the chance testing will cover existing function. The Tester would also define any facts that the model might need (for example, the name of the file to be opened and saved). The Tester then defines any goals or subgoals to be attained. A goal might be saving the file. Then the rules under which the model will operate are defined. One rule might be if the file (named as a fact) has its date and/or time changed, then the goal of saving the file was reached and the test will end.


Robert Cox Photo 3
Method And Apparatus For Character Preprocessing Which Translates Textual Description Into Numeric Form For Input To A Neural Network

Method And Apparatus For Character Preprocessing Which Translates Textual Description Into Numeric Form For Input To A Neural Network

US Patent:
5680627, Oct 21, 1997
Filed:
Feb 15, 1991
Appl. No.:
7/656883
Inventors:
Billy W. Anglea - Round Rock TX
Robert Charles Cox - Round Rock TX
Assignee:
Texas Instruments Incorporated - Dallas TX
International Classification:
G06F 1720
US Classification:
395751
Abstract:
A preprocessor translates problem descriptions in text format to a numeric form, usable by a neural network. Problem descriptions and associated solutions are used as training sets for the neural network. From a word domain collected from a number of problem descriptions, each character used in the problem domain is assigned a character frequency value. These frequency values are used to translate each problem description to an input vector, where each input value represents a character and each input value is associated with an input node of the neural network. In addition to being associated with a frequency value, each character is scaled and normalized to improve accuracy of the neural network's recall capabilities.