Automatic trace retrieval using semantic bridge

A method for performing automatic trace retrieval, comprising:

• receiving a first model for a system or service, the first model including a first plurality of model artifacts at least partially represented by a first semantic style;
• receiving a second model for the system or service, the second model including a second plurality of artifacts at least partially represented by a second semantic style;
• collecting training data including one or more correspondences between artifacts of the first plurality of model artifacts and artifacts of the second plurality of artifacts;
• generating a semantic transformation table for converting between the first and second semantic styles using the collected training data and
• using the generated semantic transformation table in tracing associations between artifacts of the first plurality of artifacts and artifacts of the second plurality of artifacts,
• wherein the first semantic style includes language for describing a regulatory environment and the second semantic style includes language for describing a software programming environment.

A method for performing automatic trace retrieval, comprising:

• receiving a first model for a system or service, the first model including a first plurality of model artifacts at least partially represented by a first semantic style;
• receiving a second model for the system or service, the second model including a second plurality of artifacts at least partially represented by a second semantic style;
• collecting training data including one or more correspondences between artifacts of the first plurality of model artifacts and artifacts of the second plurality of artifacts;
• generating a semantic transformation table for converting between the first and second semantic styles using the collected training data and
• using the generated semantic transformation table in tracing associations between artifacts of the first plurality of artifacts and artifacts of the second plurality of artifacts,
• wherein the training data further includes modified trace queries.

A method for performing automatic trace retrieval, comprising:

• receiving a first model for a system or service, the first model including a first plurality of model artifacts at least partially represented by a first semantic style;
• receiving a second model for the system or service, the second model including a second plurality of artifacts at least partially represented by a second semantic style;
• collecting one or more manually input correspondences between artifacts of the first plurality of model artifacts and artifacts of the second plurality of artifacts;
• joining artifacts of the first and second plurality of model artifacts;
• employing association rule mining to detect co-occurrences within the joined artifacts;
• establishing transformation rules from the association rule mining;
• filtering the established transformation rules to remove invalid rules;
• and
• using the filtered transformation rules in tracing associations between artifacts of the first plurality of artifacts and artifacts of the second plurality of artifacts.

A computer system comprising:

• a processor;
• and
• a non-transitory, tangible, program storage medium, readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for performing automatic trace retrieval, the method comprising:
• receiving a first model for a system or service, the first model including a first plurality of model artifacts at least partially represented by a first semantic style;
• receiving a second model for the system or service, the second model including a second plurality of artifacts at least partially represented by a second semantic style;
• collecting training data including one or more correspondences between artifacts of the first plurality of model artifacts and artifacts of the second plurality of artifacts;
• generating a semantic transformation table for converting between the first and second semantic styles using the collected training data;
• and
• using the generated semantic transformation table in tracing associations between artifacts of the first plurality of artifacts and artifacts of the second plurality of artifacts,
• wherein generating the semantic transformation table comprises using computer learning techniques to generate a thesaurus of corresponding terms from the collected one or more correspondences between artifacts of the first plurality of model artifacts and artifacts of the second plurality of artifacts.