Test automation for verifying software s detectability for rule violations
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Test Automation for Verifying Software’s Detectability for Rule Violations. Name: Zhishuai Yao Supervisor: Pro. Jukka Manner Place: Varian Medical Systems Finland Oy. Outlines. Overview and background Objectives of the thesis Design and implementation Results and conclusions Q & A.

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Test automation for verifying software s detectability for rule violations

Test Automation for Verifying Software’s Detectability for Rule Violations

Name: Zhishuai Yao

Supervisor: Pro. Jukka Manner

Place: Varian Medical Systems Finland Oy


Outlines
Outlines Rule Violations

  • Overview and background

  • Objectives of the thesis

  • Design and implementation

  • Results and conclusions

  • Q & A


Overview and background
Overview and Background Rule Violations

  • This thesis is done in a company which develops software for radiation therapy in cancer treatment

  • Automated tests are created to verify the error detecting mechanism (“checking functions”) in the software


Overview and background1
Overview and Background Rule Violations

  • Radiation therapy

    • Using radiation beam to irradiate the tumor.

    • Requires high accuracy at tumor positioning and dosing the treatment


Overview and background2
Overview and Background Rule Violations

  • Treatment planning system (TPS)

    • Computerized application used for simulate the dose distribution in CT images

    • Various of inputs to the TPS increases the risk for radiation therapy


Objectives of the thesis
Objectives of the Thesis Rule Violations

Implementing the tests is to:

  • High level: reducing the risk in radiation therapy

  • Low level: eliminating the errors in the TPS by verifying the “checking functions” in the application


Design and implementation
Design and Implementation Rule Violations

  • Testing target: “checking functions”

    • For each specific violation of rule, checking function throws error or warning message to notify the user

  • Testing method: “black box testing”

    • Generate faulty cases to violate every predefined rules and check whether the correct error or warning message is throw by the “checking function”


Design and implementation1
Design and Implementation Rule Violations

  • Challenges

    • Understand each rule (requirement) and find the proper parameter to violate the rule

    • Setting the criteria to the test

    • Short execution time and reusability (e.g. for regression testing)


Design and implementation2
Design and Implementation Rule Violations


Design and implementation3
Design and Implementation Rule Violations

  • Test procedures:

    • Importing prerequisite data

    • Running the checking function for original data

      • No error or warning should be thrown

    • Modify specific parameter

    • Running the checking function again

      • Expected error or warning should be thrown

    • Log the result


Results and conclusions
Results and Conclusions Rule Violations

  • Automated test has covered 93 rules (requirements) by the time this thesis was finalized (currently more than 120 )


Results and conclusions1
Results and Conclusions Rule Violations

  • Associated warning or error is not shown.

  • Non-related warning or error is shown in addition to the correct warning or error message.

  • Corruption in data model dependency rule.

  • Some of the mandatory attributes are not correctly configured in the system.


Thanks for your attention question answer
Thanks for your attention! Rule ViolationsQuestion & Answer


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