Dynamically configurable model-to-model transformation engine

• US 9,026,985 B2
• Filed: 12/10/2004
• Issued: 05/05/2015
• Est. Priority Date: 12/10/2004
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Cornell, Kevin J., Funk, Eric O., Nguyen, Duong B., Ruest, David
• Primary Examiner(s): COYER, RYAN D
• Application Number:
  US11/009,680
• Publication Number:
  US 20060130009A1
• Time in Patent Office: 3,798 Days
• Field of Search: 717/104, 717/106, 717/136
• US Class Current: 717/104
• CPC Class Codes: G06F 8/10 Requirements analysis; Specification techniques

Abstract

A method, system and apparatus for processing a model-to-model transformation. The method can include dynamically accepting a transformation to apply to a source model in order to produce a target model. More specifically, the method can include traversing a hierarchy for the source model and applying rules in the transformation to objects in the hierarchy to produce the target model. For instance, the traversing step can include sequentially processing a list of transform elements in the transformation. In one aspect of the invention, the processing step can include loading content extractors among the transform elements. Subsequently, other transform elements can be identified through the loaded content extractors in order to traverse the hierarchy.

Claims

1. A method for processing model-to-model transformations comprising the steps of:

selecting a source model in a transformation engine;

dynamically accepting a transformation in the transformation engine to be applied to the source model, the transformation identifying a manner in which the source model is traversed and transformed to produce a target model and comprising a container of a sequence of model transform elements, each of the model transform elements comprising one of a transformation rule, a content extractor and another container; and

,

applying the transformation to the source model in order to produce the target model by reading in a source object in the source model upon traversing a hierarchy of source objects in the source model, applying at least one of the transformation rules to the source object from among the transformation rules of said model transform elements, creating a target object for the target model upon application of the at least one transformation rule to the source object, determining if additional objects in the source object remain to be processed, extracting a next additional object from the source object upon determining that additional objects in the source object remain to be processed, reading in the next additional object from the source object, repeating the application, creation, determination, and extraction steps for all additional objects of the source object.

2. The method of claim 1, wherein said traversing step comprises the step of sequentially processing a list of model transform elements in said transformation.

3. The method of claim 2, wherein said processing step comprises the steps of:

loading content extractors among said list of model transform elements; and

,

identifying other transform elements through said loaded content extractors in order to traverse said hierarchy.

4. The method of claim 1, wherein said creation step comprises the step of conditionally executing said at least one of the transformation rules on the source object in said hierarchy to produce said target model.

5. A model-to-model transformation engine comprising:

a transformation executing in memory of a computer;

an ordered list of transform elements, each transform element comprising one of a transformation rule, a container, and a content extractor, said content extractor referencing at least one object for extraction in said element, said content extractor further referencing one other transform element in the transformation; and

,

a transform coupled to the transformation, the transform configured to act as a container to the ordered list of transform elements,

the model-to-model transformation engine executing in the memory of the computer, the model-to-model transformation engine comprising program code enabled to select a source model, to dynamically accept the transformation to be applied to the source model, the transformation identifying a manner in which the source model is traversed and transformed to produce a target model, to apply the transformation to the source model in order to produce the target model by reading in a source object in the source model upon traversing a hierarchy of source objects in the source model, applying at least one of the transformation rules to the source object from among the transformation rules of said transform elements, creating a target object for the target model upon application of the at least one transformation rule to the source object, determining if additional objects in the source object remain to be processed, extracting a next additional object from the source object upon determining that additional objects in the source object remain to be processed, reading in the next additional object from the source object, repeating the application, creation, determination, and extraction steps for all additional objects of the source object.

6. The model-to-model transformation engine of claim 5, further comprising at least one property referenced by the transformation.

7. The model-to-model transformation engine of claim 6, further comprising an execution context providing access to said at least one property reference by the transformation.

8. The model-to-model transformation engine of claim 5, further comprising at least one condition referenced by at least one of said transform elements.

9. A non-transitory machine readable storage device having stored thereon a computer program for processing model-to-model transformations, the computer program comprising a routine set of instructions which when executed by a machine causes the machine to perform the step of:

selecting a source model in a transformation engine;

dynamically accepting a transformation in the transformation engine to be applied to the source model, the transformation identifying a manner in which the source model is traversed and transformed to produce a target model and comprising a container of a sequence of model transform elements, each of the model transform elements comprising one of a transformation rule, a content extractor and another container;

applying the transformation to the source model in order to produce the target model by reading in a source object in the source model upon traversing a hierarchy of source objects in the source model, applying at least one of the transformation rules to the source object from among the transformation rules of said model transform elements, creating a target object for the target model upon application of the at least one transformation rule to the source object, determining if additional objects in the source object remain to be processed, extracting a next additional object from the source object upon determining that additional objects in the source object remain to be processed, reading in the next additional object from the source object, repeating the application, creation, determination, and extraction steps for all additional objects of the source object.

10. The non-transitory machine readable storage device of claim 9, wherein said traversing step comprises the step of sequentially processing a list of model transform elements in said transformation.

11. The non-transitory machine readable storage device of claim 10, wherein said processing step comprises the steps of:

loading content extractors among said list of model transform elements; and

, identifying other transform elements through said loaded content extractors in order to traverse said hierarchy.

12. The non-transitory machine readable storage device of claim 9, wherein said creation step comprises the step of conditionally executing said at least one of the transformation rules on the source object in said hierarchy to produce said target model.