PATENT CLAIM ANALYSIS

Application Number: 15952565
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-07
Patent Classification: ["717", "106000"]

Abstract:
A system for improving software code quality using artificial intelligence is provided. The system comprises a training data extraction module to extract learning data files from a source control management system and an integrated development environment for preparing training data. The system further comprises a machine learning model trainer that conducts training of an artificial neural network. The system further comprises a machine learning recommendation module that queries the trained artificial neural network to check for recommendations for improving quality of one or more new software codes and one or more modified software codes. The system also comprises a remediation module that determines one or more coding standard violations in the one or more new software codes and one or more modified software codes. The quality of the one or more new software codes and one or more modified software codes is improved by applying the recommendations.

Claim (Index 7):
The system of  claim 1 , wherein the training of the artificial neural network is implemented inside a deep learning framework.

Metadata:
- Claim Count in Document: 46.0
- Percentile: 91.0
- Lexical Diversity: 2.35385
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15416988', '12019060', '14948341', '10152731', '15919033']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3886430871994841
- 35 USC 102 Novelty (BERT): 0.4971733119569538
- Combined Prediction Score: 0.3994961096752311
- Mean Citation Score: 167.107786
- Max Citation Score: 192.86223
- Similarity Product: 138.58613800617815

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

Dataset: test