PATENT CLAIM ANALYSIS

Application Number: 15953650
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-10
Patent Classification: ["717", "124000"]

Abstract:
A neural network for identifying defects in source code of computer software. The neural network comprises: at least one convolutional layer configured to generate a one or more feature abstractions associated with an input segment associated with the source code; at least one recurrent layer configured to identify within the one or more feature abstractions a pattern indicative of a defect in the source code; and at least one mapping layer configured to generate a mapping between the identified pattern and a location of the indicated defect in the source code.

Claim (Index 8):
The deep learning neural network of  claim 1  wherein the identifying of a pattern is performed in accordance with contents of a memory associated with the recurrent layer.

Metadata:
- Claim Count in Document: 34.0
- Percentile: 91.0
- Lexical Diversity: 2.0
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15925010', '15664925', '15402169', '15603249', '15665330']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.339683248933235
- 35 USC 102 Novelty (BERT): 0.4634694648023236
- Combined Prediction Score: 0.3520618705201438
- Mean Citation Score: 129.80139400000002
- Max Citation Score: 137.86392
- Similarity Product: 118.46140697361946

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

Dataset: test