Amazon patents tool that labels code connections with AI scores
Amazon describes a system that uses machine learning to analyze computer code and create a map of how different functions interact. The system adds labels to this map, providing scores that estimate the likelihood of specific data flows or security risks within the code.
In the filing’s own words
Described are example systems and methods generally directed to processing program information associated with a computer program to generate an annotated call graph. The annotated call graph may include nodes that represent functions included in the program and edges that represent function calls, relationships, and/or other dependencies between the functions included in the computer program, as well as annotations associated with one or more edges and/or one or more nodes of the call graph. Each annotation may correspond to an edge or node of the call graph and may include a score that represents a strength and/or likelihood of certain features and/or characteristics of the associated edge and/or node.
What exactly they claim (claim 1)
1. A computer-implemented method, comprising: generating a plurality of training datasets that include a first plurality of program information associated with a plurality of programs; accessing the plurality of training datasets to train a machine learning model to determine annotations for a call graph; subsequent to training of the machine learning model, receiving, by the trained machine learning model, a second plurality of program information associated with a program to be analyzed by the trained machine learning model, wherein the second plurality of program information includes a static call graph having a plurality of edges and a plurality of nodes that represents the program; processing, using the trained machine learning model, the second plurality of program information to determine a plurality of function embeddings that represent a plurality of functions included in the program and encode lexical information, static information, and dynamic information associated with the program and extracted from the second plurality of program information; processing, using the trained machine learning model, the plurality of function embeddings to generate a plurality of annotations for the static call graph, wherein the plurality of annotations includes a first annotation that indicates at least one of a location of a first data object, a source node associated with a second data object, or a sink node associated with a third data object; and associating the plurality of annotations with at least a portion of the plurality of edges and the plurality of nodes to generate an annotated call graph.
Facts
- Company
- Amazon (Amazon Technologies, Inc.)
- Official title
- Generation of annotated call graphs
- Patent number
- US12761914B1
- Application number
- 18534488
- Filed
- Dec 8, 2023
- Granted
- Oct 13, 2026
- Inventors
- 2
- Claims
- 20
Classified under
G06F 8/73 Physics & computingG06F 8/75 Physics & computingMore from Amazon in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.