VerifIEr is a quality assurance tool for checking that your CA Gen models are free of errors and compliant with your standards. It includes many pre-configured checks which scan and validate your Action Diagrams and other Gen objects, as well as providing the ability to extend its set of checks to include your own specific requirements.

Most Gen sites have development standards covering aspects such as naming conventions, use of return codes, factors that affect performance, etc. Projects that out-source development activity will especially want to check the models for compliance to standards. Checking that the model meets these standards can be a time consuming task, and this is usually allocated to an experienced Gen developer to perform manually via code inspection.

VerifIEr is supplied with a set of standard check types and is also designed to be rapidly customised to meet site specific requirements, either by IET or by the customer.

Many of these checks are designed to catch coding errors in the code at an early stage in the life-cycle because errors are much easier to fix before time has been spent on generated and testing the code or handing over the code to a separate testing team.

VerifIEr can automate most compliance and QA checking tasks, thus freeing up experienced Gen developers for more value added activities. Verification checks can be performed on an entire model, selected objects or the contents of a GuardIEn Change Request, Release Pack or System Update. Automated checking means that a far greater range of checks can be performed when compared with the effort involved in manual checking.

Checks can be invoked on demand, scheduled in batch, performed automatically on upload or as part of a GuardIEn System Update.

An essential feature of VerifIEr is that QA can be enforced automatically and therefore problems are identified early in the development life-cycle. This contrasts with manual checking or ad-hoc tools where the models are checked at the end of the development phase, by which time the cost of fixing the errors is much higher compared with identifying the issues as soon as they are applied to the model, i.e. before the code has been generated and tested.