K-RASINS, as a test management system, aids in the accomplishment of organisational objectives by satisfying functional criteria via several processes. The workflows include data characteristics and paths. It’s a Test Management Services Framework that aids the doer in achieving a specific goal by completing functional requirements by following a series of steps. The workflows include data characteristics and paths.
Based on our vast experience in the QA and test management services framework, we advise using a test design methodology that outlines a simple step-by-step process to accomplish functional objectives. Let us now take a deeper look-
Requirements enumeration
Attribute enumeration
Scenario enumeration
Integration point enumeration
Node test cases enumeration
While implementing, we ensure complete test coverage, from test design to minor regressions. It encourages a stable and reliable platform, leading to highly effective software testing.
Get real test cases tailored to the specifications and provide findings close to the anticipated results.
You can expand your test coverage with K-RASINS to successfully complete most tests.
To achieve the required test results, develop the optimal test plan and carry it out using K-RASINS.
Using planned periodic micro regressions, you can ensure that the product functions correctly with the existing codes or feature updates.
K-RASINS has produced noteworthy outcomes and positively impacted projects across all verticals.
K-RASINS offers practical strategies for locating and deploying the appropriate and pertinent tests to avoid unnecessary delays that result in additional expenditures.
The impact of K-RASINS implementation continues long after the tests run because it consistently improves test cases and formalises the correct behaviour.
K-RASINS helps you evaluate the software engineering and code base for quality, longevity, and lack of scalability before providing a solution to address the findings.
One of the critical ways K-RASINS maximises return on investment is by reducing post-production errors.
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