Dependency Graph Traversal via Node Dependency Tables
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methodologies for traversing complex dependency graphs or tree structures are complex, recursive, and resource-intensive, making them inefficient for large and complex structures.
Innovation Solution
A new methodology that allows systems to traverse any tree structure or Directed Acyclic Graph (DAG) in a single, simple process without recursion, repetitiveness, stacks, or queues, thereby simplifying the code and reducing execution intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional recursive traversal methods (DFS, BFS) are used to traverse dependency graphs, then the traversal logic is well-established and proven, but the processing time and resource consumption grow exponentially with the size and complexity of the graph
Solution Approach 1:
The patent segments the dependency graph traversal into independent atomic operations by representing the graph as a collection of discrete nodes with explicit parent-child relationship tables. Each node's dependencies are independently evaluated using direct table lookups rather than recursive traversal, breaking down the complex traversal problem into simple, non-recursive atomic checks that do not accumulate processing overhead.
Solution Approach 2:
The patent performs preliminary action by pre-computing and storing the dependency relationships in structured tables (node dependency tables) that map parent-child relationships explicitly. This pre-organization of data allows O(1) direct access to dependency information without requiring recursive exploration during traversal, eliminating the need for stacks, queues, or repeated visits to nodes.
2Reliability
If recursive traversal methods are used on large, complex dependency structures, then complete coverage of all nodes is achieved, but the memory usage and execution resources increase dramatically
Solution Approach 1:
The patent creates a simplified copy of the dependency structure in the form of node dependency tables that explicitly list parent-child relationships. Instead of traversing the original complex graph structure recursively, the system uses these simplified table representations to determine dependencies through direct lookup, avoiding the memory overhead of recursion stacks and repeated node visits while maintaining complete dependency coverage.
3Reliability
If traditional graph traversal methodologies are implemented, then all parent-child relationships are identified, but the code complexity and implementation steps increase significantly
Solution Approach 1:
The patent extracts the dependency relationship information from the complex graph structure and places it into simple, dedicated node dependency tables. This extraction separates the relationship data from the traversal logic, allowing dependencies to be queried through straightforward table lookups rather than complex recursive algorithms, thereby dramatically simplifying the code while maintaining accurate relationship identification.
4Reliability
If recursive traversal is used to validate child node dependencies, then all dependencies are checked, but the processing becomes repetitive and visits nodes multiple times
Solution Approach 1:
The patent performs preliminary action by pre-organizing dependency information in node dependency tables that explicitly define parent-child relationships. This allows the system to validate dependencies through direct table lookups without repetitive recursive traversal, ensuring each node's dependencies are checked exactly once through efficient O(1) operations rather than multiple visits during recursive exploration.
Data Source
AI summary
In some aspects, techniques can be performed by a processor of a computing device, the method can include receiving an input selecting a first node instance of a first node. The method can include accessing a node dependency table listing one or more parent nodes and child nodes for the selected first node instance. The method can include determining if dependencies for the selected first node instance are met by accessing a node process log. The technique can include running the first node when the dependencies for the selected first node are met. The technique can include updating the node process log.