Lucent Technologies Inc.

James R Rowland

Thaddeus Julius Kowalski

James E Goodnow, Ii

Jonathan Isaac Helfman

Carl Robert Seaquist

John J Puttress

Maria Jesus Peman

Techniques for optimizing decision making apparatus by instrumenting the apparatus and running it on test data which has the characteristics of the data upon which the decision making apparatus is to be used. The information provided by the instruments is then used to reorder the application of the criteria used by the decision making apparatus to the data. The techniques are applied in rule-based system which employs a decision network to evaluate the rules. The decision network is instrumented and the rule-based system is run on the test data. The results returned by the instrumentation are used to determine how to rearrange condition elements in the rules so that the flow of data through the decision network is minimized. The condition elements are then rearranged in that fashion and the modified rule-based system is employed on real data.

Methods and apparatus for optimizing decision making

A method of analyzing a plurality of code segments to determine the similar static and dynamic features of the code segments compares the static and dynamic features of each of the code segments. Each code segment is comprised of one or more lines of program instructions. One or more predetermined static attributes are extracted from each code segment. Each code segment is then run so that the dynamic attributes of the code segment can be determined. The dynamic attributes are extracted from each code segment and a distance function is computed which is based on the extracted static and dynamic attributes for a given pair of code segments. The distance function produces a distance measurement which indicates the relative degree of similarity between the given pair of code segments.

Method of identifying similarities in code segments

Disclosed is a software generation system (SGS) based memory error detection system which may be utilized to detect various memory access errors, such as array dimension violations, dereferencing of invalid pointers, accessing freed memory, reading uninitialized memory, and automated detection of memory leaks. Error checking commands and additional information are inserted into a parse tree associated with a source code file being tested at read-time which serve to initiate and facilitate run-time error detection processes. Wrapper functions may be provided for initiating error checking processes for associated library functions. A pointer check table maintains pointer information, including valid range information, for each pointer that is utilized to monitor the use and modification of the respective pointers. A memory allocation structure records allocation information, including a chain list of all pointers that point to the memory region and an initialization status for each byte in the memory region, for each region of memory. The chain list is utilized to monitor the deallocation of the associated memory region, as well as to detect when there is a memory leak. The initialization status is used to ensure that a region of uninitialized memory is not accessed. A data flow analysis algorithm minimizes the number of pointer checks that have to be performed and allows certain read-time errors to be detected.

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Short Hills, NJ, United States of America

James R Rowland