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15 Usability Tests.md

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15 USABILITY TEST CASES

  1. Verify whether the landing page is intutive enough for user to get directed to their logins (doctor and patient separate) (YES)

  2. Verify whether the login page took only required necessary inputs. (YES)

  3. Verify whether the directing for the sign up process in case an account does not exists is already easy (YES)

  4. Verify whether the sign up page took only necessary inputs to create an account. (YES)

  5. Verify whether the page is displayed correctly after the login with the users' own account. (YES)

  6. Verify whether the map shown covers the exact neigbourhood areas of the user and the pointers marked at doctors are correct. (YES)

  7. Verify whether on the doctors' login, accuracy testing page displays the results correctly and clearly, thus making it easier to analyse the accuracy of any disease data.

  8. Verify whether the 'Register Here!!' page has all necessary text boxes to create account (First Name, Last Name, Email Address, Password). (YES)

  9. Verify whether there are subjective metrics (if there isn't any, one should start including the basic ones, like presets). (YES)

  10. Verify whether Symptom, Value, and Symptom Description have right ranges and parameters (inclusive/exclusive). (YES)

  11. Verify whether there is a navigation flow as a basic principle of heuristic evaluation for first time users. (YES)

  12. Verify whether for each and every disease, there is it's respective severity, a prediction result and precaution page(HTML). (YES)

  13. Verify whether the disease knowledge base (for add disease) has disease name, specialist and precautions dialog box in working condition with features to add symptom details. (YES)

  14. Verify whether the fuzzy logic algorithm is consistent in it's results (output) for the same symptoms (input parameters) through a dry run. (YES)

  15. Verify whether there is an option to save the details, or logout on the required pages and modules, with a weight of symptom for each characteristic as a measure of transparency of how the system predicts. (YES)