Massachusetts Institute of Technology

Bae Systems Information and Electronic Systems Integration Inc.

Seque Software, Inc.

Timothy Alan Anderson

Martin Conway Rinard

Stylianos Sidiroglou

Jeff Herbert Perkins

David C Laroche

Paolo Mario Piselli

Basil C Krikeles

Eric Patrick Lahtinen

Greg Timothy Sullivan

An approach to detection and repair of application level semantic errors in deployed software includes inferring aspects of correct operation of a program. For instance, a suite of examples of operations that are known or assumed to be correct are used to infer correct operation. Further operation of the program can be compared to results found during correct operation and the logic of the program can be augmented to ensure that aspects of further examples of operation of the program are sufficiently similar to the examples in the correct suite. In some examples, the similarity is based on identifying invariants that are satisfied at certain points in the program execution, and augmenting (e.g., 'patching') the logic includes adding tests to confirm that the invariants are satisfied in the new examples. In some examples, the logic invokes an automatic or semi-automatic error handling procedure if the test is not satisfied. Augmenting the logic in this way may prevent malicious parties from exploiting the semantic errors, and may prevent failures in execution of the programs that may have been avoided.

Automatic correction of program logic

A method of recognizing graphical objects by subjecting the graphical information gathered through 'spying' to a series of rules by which the object becomes understood or recognized as an instance of a standard logical object. Before the rules are applied, graphical objects are first interpreted as primitives including groups of text, lines and images. In order to recognize a graphical object as a logical object, the graphical information is subjected to the rules in an iterative process whereby an understanding of the object is continually refined. As the rules are applied, the results are evaluated to determine whether the graphical object can be 'mapped' to a standard logical object such as a textfield or listbox. Once the object is understood as a logical element with which the user is accustomed, it is possible to interact with the object and obtain data from the object as if it were a standard object with a published interface. By subjecting the graphical data to a series of rules designed specifically to recognize tables, the boundaries and the internal structure of rows and columns will be understood. Once the graphical data is recognized as a table, the data which it contains in rows can then be accessed. By classifying an object as an instance of a known object, assumptions can be made about the object so that it can be navigated or validated by sending events or messages.

Application testing with virtual object recognition

Growing community of inventors

Sudbury, MA, United States of America

Timothy Alan Anderson