Telcordia Technologies, Inc.

Tti Inventions C LLC

Tt Government Solutions, Inc.

Hiralal Agrawal

Munir Cochinwala

Ashish Jain

Devasis Bassu

Clifford Behrens

James L Alberi

Balakrishnan Dasarathy

Joseph R Horgan

Rabih Zbib

A system and method for automated determination of quasi-identifiers for sensitive data fields in a dataset are provided. In one aspect, the system and method identifies quasi-identifier fields in the dataset based upon a static analysis of program statements in a computer program having access to&#x2014;sensitive data fields in the dataset. In another aspect, the system and method identifies quasi-identifier fields based upon a dynamic analysis of program statements in a computer program having access to&#x2014;sensitive data fields in the dataset. Once such quasi-identifiers have been identified, the data stored in such fields may be anonymized using techniques such as k-anonymity. As a result, the data in the anonymized quasi-identifiers fields cannot be used to infer a value stored in a sensitive data field in the dataset.

Automated determination of quasi-identifiers using program analysis

A method is provided for generating a test case for testing a program, which can include analyzing instructions of the program to identify basic blocks and superblocks, each basic block containing at least one executable instruction, and each superblock containing a plurality of basic blocks. The method can include executing instructions by a processor to perform determining respective weights of superblocks, each weight representing a number of basic blocks which require execution when the superblock is executed; determining the constraints which cause a superblock having a high weight to be executed, and using the determined constraints to generate a test case which, upon execution of the program, causes the high weight superblock to be executed.

Automated testing of software with targeting of deep paths

A computer-enabled method of learning the behavior of a program. A processor can execute a target program during a learning interval while varying a plurality of stimuli provided to the target program so as to produce a multiplicity of different sequences of events which differ in combinations of types of events in respective sequences, orders in which the types of events occur in respective sequences, or in the combinations and in the orders in which the types of events occur. The multiplicity of event sequences can be recorded, and a second program can be executed by a processor to: determine a plurality of clusters based on similarities between the event sequences in their entirety; and determine a plurality of signatures corresponding to the plurality of clusters. Each signature can be the longest common subsequence of all sequences in the respective cluster and thus representative of the cluster. In such method, each of the plurality of signatures can be a benchmark representative of acceptable behavior of the target program.

Learning program behavior for anomaly detection

The present invention concerns methods and apparatus for implementing a model-based paradigm for use in developing systems of software solutions. In a method of the present invention, a developer defines templates for use in creating software architecture elements which comprise a software solution or a system of software solutions. The template definitions comprise specifications of template attributes. The developer specifies relationships and dependencies among the templates using a computer programmed to receive the template definitions.

Methods and apparatus for implementing model-based software solution development and integrated change management

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Bridgewater, NJ, United States of America

Hiralal Agrawal