Versata Development Group, Inc.

Trilogy Development Group, Inc.

Other

Shawn A P Smith

Daniel Paul Karipides

Brandon M Beck

Andrew Maag

Douglas Stephen Fearing

Jeffrey W Ragusa

A log file processing system sorts records from large log files and groups them by session without making a complete copy of the log files by capturing a subset of the log files in a sliding memory window and identifying all records in the window that form a complete user session. Records belonging to a complete session are output for analyzing, and the remaining records are output as raw log data for additional processing. Using a ring buffer to implement the sliding memory window, data structures are used to group records by session, to identify completed sessions, and to index into the ring buffer to retrieve records for completed sessions that are to be directly analyzed. Any records remaining in the ring buffer at the end of slide window processing may be output as raw log file data and are processed as incomplete or malformed session records. An embodiment of the log file processing system provides a significant improvement on the speed of data extraction from log files into analyzable session data.

Session-based processing method and system

A model consolidation process combines multiple configuration models into a single unified configuration model that contains the union of the allowable combinations (i.e. combinations that are buildable) from each of the original models. An aspect of at least one embodiment of the model consolidation process is that it allows models to be combined in such a way that any incompatibilities or contradictions between models are detected and automatically resolved where possible. If an incompatibility is detected that cannot be automatically resolved, then the configuration models should not be combined. Instead if this incompatibility case occurs, at least one embodiment of the model consolidation process produces a description of the problem encountered and report the problem along with the necessary information required for a human to resolve it.

Consolidation of product data models

Configuration spaces facilitate the useful presentation of data, particularly configuration data used for representing configured products. Products include features and common features can be grouped by families. For example, an automobile can include a transmission family. The transmission family could include features such as automatic transmission and 4-speed manual transmission. Configuration spaces can be achieved by consolidating selected data without loosing useful information. The degree of consolidation achieved can be significant enough to permit display of data using conventional display technology. Configuration spaces break down the 'universe' of possible configurations into constituent spaces defined by groups of rules for a selected feature. Common dependencies between the selected feature and related features can be consolidated to produce a more minimal form of the data used for representing the selected features and related features. Configuration spaces can provide a useful graphical view of the breakdown of all rules written for a single feature or multiple features. The data present in this view can be analyzed to, for example, study the dependency paths of an existing configuration and better understand the impact of revising configuration relationships. Thus, configuration spaces aid in the creation and modification of configuration models.

Configuration representation and modeling using configuration spaces

Inconsistencies between configuration rules represent a significant concern when modeling a product using configuration rules. The consistency checking system approaches a configuration model from the perspective of a sets of features and families. The configuration space of a model represents the entire set of all combinations of selections within a configuration model. The consistency checking system operates on subsets of the configuration space by consolidating data within the configuration space into minimized subsets that represent a portion of the configuration space where a particular consistency error can occur. Thus, the contents of each subset vary depending upon which consistency error is being checked, and consistency checking is performed on reduced subsets determined on an error by error basis rather than on the configuration space as a whole.

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Austin, TX, United States of America

Shawn A P Smith