Fault Localization Techniques in SEObjective 1: Survey of all Techniqu, Assignments of Software Engineering

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Fault Localization

Techniques in SE

Objective 1: Survey of all

Techniques

Objective 2: Areas of

improvement

• (^) Section 3 – Advanced Techniques
  • (^) Slice Based Techniques
    • (^) Static slicing
    • (^) dynamic slicing
    • (^) execution slicing
  • Delta Debugging – simplify down inputs (diagram)
  • (^) Coverage Based Approaches – Program spectra, Program spectrum based methods (diagram), Suspiciousness Score
  • Mutation Based Techniques
    • (^) MUSE,
    • (^) Metallaxis
  • Reasoning Based Approaches
    • (^) Model Based Diagnosis
    • (^) Model Based Software Debugging
      • (^) Dependency Based Models
      • (^) Abstraction Based Models

Objective 2: How can we improve?

• (^) Section 3 (F,G)
  • (^) Machine Learning Based Approach – BP neural network, C4.5 decision tree, SVM – faulty and non faulty classification
  • (^) Data Mining Based Approach – some data can’t be found manually by analysis, sorting of N-Grams
• (^) Section 4 – Important Issues and Improvement areas
  • Effectiveness of FL method – effectiveness score
  • (^) Clustering for programs with multiple bugs – single bug-multiple bugs, fault focusing clusters
  • (^) Impact of test cases – subset of testcases, previous-current testcase, coincidental correctness – Eg. Variable value overwritten
  • Faults introduced by missing codes – unable to find “faulty” code because it is missing