Summary: Thesis Version 24Dec 21

Read the summary and the most important questions on Thesis Version 24Dec 21

• 1 1.1 Overview of Research

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• What is Continuous Integration (CI) and how does it benefit software development organizations?

  - Continuous Integration (CI) allows more frequent integration of software changes
  - Faster and more cost-effective software evolution
  - Eliminates integration issues early
  - Enhances collaboration among developers
  - Increases software quality and efficiency
  - Supports agile development practices

• What is regression testing and why is it time-consuming during the integration cycle?

  - Part of integration cycle, also known as a software build
  - Includes a significant number of tests in a test suite
  - Test execution can take hours or days
  - Tests the entire system for any regressions or bugs

• How does Test Case Minimization (TCM) differ from Test Case Selection (TCS) in terms of optimizing tests?

  - TCM removes unnecessary (redundant) test cases
  - Reduces the size of a test suite based on defined benchmarks
  - TCS selects a collection of test cases effective for the modified portion of a System Under Test (SUT)

• What are the benefits and limitations of using Neural Networks for test case prioritization according to the provided data?

  - Benefits of using Neural Networks include continuous actions, adaptiveness, and test cases prioritization efficiency.
  - Limitations involve the need for a long history of tests, more data processing, and ineffectiveness if the test history is insufficiently long.

• How do Genetic Algorithms benefit test case prioritization and what are their limitations?

  - Advantages of Genetic Algorithms are adaptiveness, simplicity, considering severity of faults, execution time, structural coverage, and greater efficiency than non-adaptive approaches.
  - They struggle with scaling on complexity and lack optimization without sufficient execution time for test cases.

• What is the impact of using SVM for test case prioritization and what are its drawbacks?

  - SVM enhances prediction results through different kernel functions and requires less computational power.
  - It is not well-suited for large software metric quantities.

• Why is there a need for effective techniques considering constraints like testing budget, restricted resources, and CI environmental constraints in each test build?

  - Existing TCP techniques can be used in CI development
  - Proposed CI techniques require modifications for constraints
  - Limitations on time, budget, and resources in CI environment
  - Effective technique needed considering all constraints for each test build

• Enumerate the benefits and limitations of employing K-means for test case prioritization.

  - K-means excels in large scale testing.
  - Its drawbacks include a dependence on the initial values.

• What are the benefits and limitations of LSTM as listed in the table?

  - LSTM is proficient in retaining information over long periods.
  - However, it has a longer training period and requires more memory to train.

• What is the goal of Test Case Prioritization (TCP) in the context of Machine Learning applications?

  - Reduce the cost of regression testing
  - Maximize test suite fault detection capability
  - Minimize time and effort needed for regression testing
  - Develop realistic solutions to address challenges in regression testing