PATENT CLAIM ANALYSIS

Application Number: 15877397
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-06
Patent Classification: ["717", "136000"]

Abstract:
Providing an instruction-set simulator and a method for generating such simulator that is capable or guaranteeing the full restoration of source program file from the binary executable program, in which the generated source program is easy to analyze, and the simulation speed is considerably fast.

Claim (Index 5):
The instruction-set simulator according to  claim 4 , wherein the subroutine-call instruction output means comprises\n a machine instruction subroutine address table generation means that generates a machine instruction subroutine address table whose table entry is composed of a subroutine name and a subroutine address in the binary executable program, a subroutine address search program generation means that generates a program which searches for the subroutine address in the generated source program from the subroutine address in the binary executable program, and a data-dependent subroutine-call instruction generation means that generates data-dependent subroutine-call instructions in the generated source program in which the target call address of the data-dependent subroutine-call instruction is resolved by the subroutine address search program.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 86.0
- Lexical Diversity: 1.2973
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['13747968', '10676998', '11862030', '12485679', '10315877']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4319025635484144
- 35 USC 102 Novelty (BERT): 0.5205823883547092
- Combined Prediction Score: 0.4407705460290438
- Mean Citation Score: 246.825788
- Max Citation Score: 270.15637000000004
- Similarity Product: 184.8548657587892

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test