Code Path Permutation Reduction via Predicate Constraint Tracking
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Solution Overview
Problem
Existing methods for evaluating and optimizing code paths in computer programs are inefficient due to the exponential scaling of possible paths with the number of branches, making it impractical to exhaustively consider all possible data paths, especially when many paths are impossible or unexecuted.
Innovation Solution
The method involves tracking predicates and storing assumed constraints to eliminate impossible paths by duplicating the path visitor for each possible predicate value, allowing the traversal of only deterministic paths, thereby reducing the number of paths that need to be explored.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all possible code paths are considered exhaustively, then complete code analysis is achieved, but the complexity and time required scale exponentially
Solution Approach 1:
The patent extracts and eliminates impossible code paths by tracking predicate constraints and removing paths that violate these constraints. This allows the system to focus only on feasible execution paths, reducing the exponential complexity while maintaining analysis completeness for actual executable paths.
Solution Approach 2:
The patent performs preliminary analysis by tracking predicate constraints before full path exploration. By determining which paths are impossible based on constraint tracking, the system prepares a filtered set of only possible paths to explore, avoiding the need to examine all exponential paths.
2Reliability
If all possible code paths are explored, then comprehensive testing coverage is achieved, but execution time increases exponentially
Solution Approach 1:
The patent removes impossible paths from consideration by tracking predicate constraints. This extraction of infeasible paths allows testing to focus only on actually executable paths, maintaining comprehensive coverage for valid paths while dramatically reducing the time required compared to exhaustive exploration.
Solution Approach 2:
The patent changes the parameter of path feasibility by using constraint tracking to determine which paths are possible. This allows the testing system to adjust its exploration based on predicate constraint satisfaction, time-consuming paths that violate constraints are eliminated, reducing overall execution time while maintaining coverage for feasible paths.
3Loss of information
If redundant path tracking is performed, then complete predicate analysis is achieved, but computational resources are wasted on impossible paths
Solution Approach 1:
The patent extracts and eliminates paths that fail to satisfy predicate constraints. By tracking constraints and removing impossible paths early in the analysis process, the system avoids wasting computational resources on paths that cannot be executed, while maintaining complete predicate analysis for feasible paths.
Solution Approach 2:
The patent performs preliminary constraint tracking to determine path feasibility before full analysis. This preliminary action identifies which paths should be discarded based on predicate constraints, preventing unnecessary computational resources from being consumed on impossible paths while preserving complete analysis of possible paths.
Data Source
AI summary
Systems, methods, and computer-readable media are provided for reducing a number of potential code paths such that it is feasible to examine all possible code paths within source code. Source code may be received. The source code may be traversed such that the path is recorded. Predicates may cause the path to split such that both paths can be traversed with the result of the predicate stored such that the path does not need to split again when encountering a new predicate for which the stored predicate is determinative. The determined paths can then be used by applications.