Message Parser Runtime Choices Using Frequency Guide Fields
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Solution Overview
Problem
The existing message parsing technologies face inefficiencies when dealing with choice constructs in message models, leading to excessive parsing and high CPU costs due to the need to parse each possible structure until a correct one is found.
Innovation Solution
A system and method that includes a processor, memory, and storage medium with program instructions to parse a message against a message model by locating a choice block with a guide field, determining the most frequently occurring element options, and further parsing against the chosen option, optimizing the parsing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the runtime parses the structure as each of the plurality of possible structures in turn, then the correct structure can be found, but excessive parsing and CPU cost occur
Solution Approach 1:
The system performs preliminary actions by analyzing message frequency data before parsing to determine the most frequently occurring element option for a given guide field value. This pre-computed knowledge is stored and used during runtime to directly select the most likely element option without trying multiple structures, thereby maintaining parsing accuracy while dramatically improving parsing efficiency and reducing CPU cost.
2Measurement precision
If multiple element options are parsed in sequence, then the correct element option is identified, but parsing overhead increases
Solution Approach 1:
The system implements feedback by using frequency analysis results from processed messages to guide the parsing of subsequent messages. The element option chooser uses this feedback information (frequency data) to select the most probable element option, thereby identifying elements accurately while minimizing parsing time by avoiding unnecessary trial parses of less likely options.
Data Source
AI summary
This invention relates to a system, method and computer program product for parsing a message against a message model, the message model including a choice block of element options and guide field for guiding the parse, the method including: parsing a message against a message model until the choice block of element options and associated guide field is located in the message model; determining element options associated with a particular guide field value located in the message, each element option having an associated frequency of occurring within a body of messages; choosing the most frequently occurring element option for the located guide field value; and further parsing the choice block of element options against the chosen element option.