Quality assurance is an essential part of any business activity at RedCell Technologies. Right from the conception of a project to its delivery, we strictly adhere to our time-tested procedures to ensure that all work is conducted in compliance with best practices and industry standards. We employ a series of technical methods and measures, conduct formal technical reviews, and perform planned software testing as part of our quality policy.
Software Quality Assurance
Software engineering process data needs to be collated and disseminated to conduct proper software quality assurance. Our SQA department exercises SQA (software quality assurance) team testing, which includes a series of formal technical reviews, testing strategies and techniques, procedures for change control, procedures for assuring compliance to standards, and measurements and reporting mechanisms. Timely software reviews ensure that errors are negated right in the nascent stage when they are comparatively inexpensive to correct.
Quality Assurance teams
Our quality assurance (QA) team assists the project team in adhering to the quality commitments, performing a set of activities that address quality assurance planning, oversight, record keeping, analysis, and reporting.
Each time a project is handed over, the project team narrows down on a process for the work to be performed while the QA team reviews the process description for compliance with organizational policy, internal software standards, externally imposed standards, and other parts of the project plan.
The QA team audits and reviews selected work products, and identifies, documents and tracks deviations from the process before verifying that relevant corrections have been made. The team ensures that deviations in either the processes or the products are always documented for future reference and handled according to a set procedure. Deviations encountered in the project plan, process description, applicable standards, or end-products are then tracked till resolved.
The SQA team works towards improving the quality of the product and of the software processes itself utilizing relevant software reliability models that allow collated defect data to be extrapolated into projected failure rates and reliability predictions.
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