Exploiting Implicit Beliefs to Resolve Sparse Usage Problem in Usage-based Specification Mining

  • Main
  • Collected Data
    • Client Code Corpus
    • Ground-truth of Preconditions
  • Result Analysis
    • Accuracy
    • Characteristics of Mined Preconditions
      • Correctly Mined Preconditions
      • Incorrectly Mined Preconditions
      • Missing Preconditions
    • Effectiveness of Single Components
      • Count Controlled Loop (CCL)
      • Object Instance Creation (OIC)
      • Type Comparison (TC)
      • Null Derefrence (ND)
      • Short Circuit Evaluation (SCE)
      • Local Exception (LE)
      • 1-Level Control Flow Analysis (1-CFA)
  • Figures and Tables
    • Figure 9. Dataset
    • Figure 10. Accuracy
    • Table 1. Correctly-mined preconditions
    • Table 2. Incorrectly-mined preconditions
    • Table 3. Missing preconditions
    • Table 4. Improvement for single components
    • Figure 11. Accuracy of Count Controlled Loop (CCL)
    • Figure 12. Accuracy of Object Instance Creation (OIC)
    • Figure 13. Accuracy of Type Comparison (TC)
    • Figure 14. Accuracy of Null Dereference (ND)
    • Figure 15. Accuracy of Short Circuit Evaluation (SCE)
    • Figure 16. Improvement in precision of Local Exception (LE)
    • Figure 17. Accuracy of 1-Level Control Flow Analysis (1-CFA)

Figure 9. Dataset

Figure 10. Accuracy

Table 1. Correctly-mined preconditions

Table 2. Incorrectly-mined preconditions

Table 3. Missing preconditions

Table 4. Improvement for single components

Figure 11. Accuracy of Count Controlled Loop (CCL)

Figure 12. Accuracy of Object Instance Creation (OIC)

Figure 13. Accuracy of Type Comparison (TC)

Figure 14. Accuracy of Null Dereference (ND)

Figure 15. Accuracy of Short Circuit Evaluation (SCE)

Figure 16. Improvement in precision of Local Exception (LE)

Figure 17. Accuracy of 1-Level Control Flow Analysis (1-CFA)

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