17808204. TEST CASE GENERATOR USING AUTOMATION LIBRARY OF AN INFORMATION HANDLING SYSTEM simplified abstract (Dell Products L.P.)

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TEST CASE GENERATOR USING AUTOMATION LIBRARY OF AN INFORMATION HANDLING SYSTEM

Organization Name

Dell Products L.P.

Inventor(s)

Suren Kumar of Bangalore (IN)

Thanuja C of Bangalore (IN)

TEST CASE GENERATOR USING AUTOMATION LIBRARY OF AN INFORMATION HANDLING SYSTEM - A simplified explanation of the abstract

This abstract first appeared for US patent application 17808204 titled 'TEST CASE GENERATOR USING AUTOMATION LIBRARY OF AN INFORMATION HANDLING SYSTEM

Simplified Explanation

The abstract of this patent application describes a method for generating code files for test cases on information handling systems using natural language processing and machine learning algorithms. Here is a simplified explanation of the abstract:

  • The method involves receiving a test case that consists of multiple tasks.
  • A machine learning algorithm is used to identify a subset of code segments from pre-existing test cases in a code library that match the tasks in the test case.
  • An indication of the identified code segments is generated for re-use in the current test case.

Potential Applications

This technology has potential applications in various fields, including:

  • Software development: It can be used to automate the generation of code files for testing software systems.
  • Quality assurance: It can assist in creating test cases for ensuring the functionality and reliability of information handling systems.
  • System integration: It can help in testing the compatibility and interoperability of different components in a system.

Problems Solved

This technology addresses the following problems:

  • Manual effort: It reduces the manual effort required to create code files for test cases by automatically generating them.
  • Time-consuming process: It speeds up the process of generating test cases by utilizing pre-existing code segments.
  • Code reusability: It promotes code reusability by identifying and reusing relevant code segments from pre-existing test cases.

Benefits

The use of this technology offers several benefits:

  • Efficiency: It improves the efficiency of test case generation by automating the process and leveraging machine learning algorithms.
  • Accuracy: It enhances the accuracy of test cases by utilizing code segments that have been previously tested and validated.
  • Cost-effectiveness: It reduces the cost associated with manual test case creation and maintenance by reusing existing code segments.


Original Abstract Submitted

Code files for performing test cases on information handling systems may be generated from pre-existing test cases using natural language processing and/or machine learning algorithms. For example, a method may include receiving a test case comprising a plurality of tasks; identifying, by inputting the test case into a machine learning algorithm, a subset of code segments from code segments of at least one pre-existing test case in a code library matching at least one task of the plurality of tasks in the test case; and generating an indication of the subset of code segments for re-use from the at least one pre-existing test case for the test case.

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