Are you sure that your new systems will fully deliver on these promises?

Clearly, only end-to-end testing can tell. Setup of a robust test environment followed by high quality testing services:

• As new releases are being prepared, concurrent testing of multiple release levels and ongoing production support along with fix testing.

• Using test drivers to fill message queues with simulated meter data including a spread of exception conditions.

• Simulating AMI vendor protocols through protocol simulators that inspect requests delivered from the test-system for proper form, and produce various responses representing normal and exception based operations.

• Running test cases for various inputs with evaluation scripts that make sure that the system is processing input cases as expected.

• Executing test cases for various outputs with output message queue and file inspectors that ensure that the system is generating expected outputs for each case.

Through test drivers, test cases, and testing ‘best practices,’ the Marlabs Independent Verification & Validation (IV&V) practice provides a solid foundation for the initiative. Our test environments support rigorous testing at multiple release levels including ‘fix’ support for the production system.

Specific offerings include:

• Testing framework of reference data that is sourced from the related system of record.

• Standalone testing with ‘test drivers’ and integration testing by interfacing test systems for various applications that are coordinated with common starting conditions.

• SOA standalone testing with test drivers presenting service requests to the MDM being tested with various test cases.

• Backend AMI adapters that interface with AMI simulators that can respond to requests in the same manner as the MDM.

• Integration testing that populates various systems with common IDs for services or service points that will be used for testing.

• Cross referencing service points in the MDM database to real meters that are part of ‘test rigs’ used for testing.

• Generating simulated test meter data to represent every possible test condition, with the volumes and arrival rates that represent various operational conditions including ‘catch up’ scenarios such as ‘storm recovery’ situations.

• Database scripts for testing reports that inspect end-results to determine if results match expectations for the test scenarios.

The result is a mechanism to maximize return from your investment in AMI and MDM while averting costly errors that can lead to significant loss of revenue or customer goodwill.