Confirmation Testing

QA Valley performs Confirmation Testing to validate that previously reported defects have been remediated in new builds and sprints.  The test scenarios or test cases that originally generated these defects are repeated in precisely the same sequences and observing the same behavioral interventions and data input.  Confirmation Testing validates that the defects reported in the previous defect log have been successfully rectified, and once confirmed the corresponding defects are eliminated or flagged as rectified in the bug tracking system.

Confirmation Testing is repeated for every new Agile Sprint to validate that the defects reported in the last test cycle or software build can now be closed and that the assigned developers can advance ahead in the overall project plan.  QA Valley assimilates step by step recordings of the test scenarios or test cases as defendable evidence that the corresponding defects were resolved.  The intent is to validate defect elimination and be able to substantiate closure with repeatable steps under the same conditions and on the same environment.

Defects that fail confirmation continue to remain in the defect log or bug tracking system, but are flagged for rectification in the next development sprint or build.  Defects that recur through multiple sprint cycles are marked for particular attention.  This enables the QA Manager and the Project Manager to trace the root causes for repeated appearance of offending defects.  This frequently means that the true symptoms of these defects have not been effectively established and that developers may be misdirecting their programming efforts.

Retesting reports and statistical summaries are produced at the end of each cycle of Confirmation Testing, reporting critical performance indicators such as number of defects retested and closed, and the number of repeat defects marked for special attention.  Furthermore, QA Valley classifies defects according to modules and functions so that Project Managers and QA Managers can better identify the aspects of the software or application that may be more programmatically challenging, and that may demand deeper skills and talent to stabilize.