International Business Machines Corporation

Bert Vincent Laonipon

Carolyn Haibt Norton

Robbie John Minshall

Srinvasan K Rangaswamy

Lawrence H Koved

Matt Richard Hogstrom

David Granshaw

Simon Christopher Nash

Aaron Stephen Jay Kershenbaum

Ann Eleanor Dalton

Marco Pistola

A method in a data processing system for detecting and reducing database contention and deadlock caused from within an application server. A determination is made as to whether a set of parameters in a statistical model indicates contention. If the set of parameters in the statistical model indicates contention, an application server administrator is notified of the contention and the number of threads in an application server pool is reduced. If the set of parameters in the statistical model indicates contention is reduced, the number of threads in the application server pool is increased.

Database contention and deadlock detection and reduction within application servers

A method, system and apparatus for performing selective data processing based upon a static analysis of the code of a compiled object. A compiled object, for example an enterprise bean, can be analyzed to determine how individual methods in the enterprise bean access specific objects. Those specific objects can include, for instance, data members of a class, or class objects passed into one or more individual methods of the enterprise bean. Where the individual methods of the enterprise bean do not mutate or otherwise change the state of the specific objects, those objects can be accessed by reference only. Importantly, where the specific objects are data fields linked to a table in a database as managed by a container managed persistence (CMP) bean, an update to the table will not be required when the static analysis of the enterprise bean otherwise indicates that the data fields are merely accessed, but not updated.

Code analysis for selective runtime data processing

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Raleigh, NC, United States of America

Bert Vincent Laonipon