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Comment: Published by Scroll Versions from space DTPDEVEL and version 5.4.0

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  1. Anchor
    step1-checkin
    step1-checkin
    Developers edit and commit source code files to source control. 
  2. Anchor
    step2-prepcsv
    step2-prepcsv
    A special CSV file that maps files to requirements is prepared, e.g.:

    FileAssociated Requirement ID

    Project-A/src/foo/goo.java

    reqA

    Project-A/src/foo2/goo.c

    reqA, reqB, reqC
    Info
    titleCreating the File-to-Requirement Map

    The file may be prepared manually be team members or it can be automated with a script. For example, the script could scan the source control repository for requirements markers added by developers and generates the CSV file accordingly.

  3. DTP Engines or SOAtest Parasoft code analysis and test execution tools analyze the source code with static analysis or metrics analysis. The analysis run must be run with the specific build ID and filter ID (see the documentation for the tool for instructions on how to specify these IDs). The purpose of this run is to feed the DTP database with information about files committed to the source control system for the specific build ID (see step #1). 
  4. Run the CSV-scanning script shipped in the DTP_HOME\grs\extras\traceability directory with the following arguments:

    Code Block
    groovy fileReqAssoc.groovy -csv <CSV_FILE_NAME> -build <BUILD_ID> -dtp <DTP_HOST_INC_PROTOCOL> -user <DTP_USERNAME> -password <DTP_PASSWORD>

    This is an example script intended to demonstrate a sequence of API calls that should be performed to associate files with artifacts in DTP. You can use this example script as a starting point for implementing a more advanced solution.

    The script is written in Groovy, but the directory also contains a JAR file that you can run with the same arguments.

    The script scans the CSV file prepared in step #2 and feeds the DTP database with the information about requirements to files mapping. See the README.txt file for details how to run the script.

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