Data Transformation Program Entropy Maximization
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Solution Overview
Problem
Programming By Example (PBE) technologies face inefficiencies in generating programs that produce desired output data, leading to excessive computational resource waste due to the need for repeated program regeneration when dealing with increased combinations of input and output data examples.
Innovation Solution
A data transformation program that generates multiple programs transforming input data into output data with varying transformation processes, and identifies second input data that maximizes the entropy of output data, using graph search and the A* algorithm to optimize program generation and reduce user burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of examples of combinations of input data and output data is increased to improve program generation accuracy, then the reliability of output data improves, but the computational resources consumed increase and productivity decreases
Solution Approach 1:
The system performs preliminary analysis of the input-output data space to identify high-entropy regions before actual program generation. By pre-calculating which input data combinations are most informative (have highest entropy), the system avoids盲目ly testing all possible combinations, thus improving reliability while maintaining productivity
Solution Approach 2:
The system changes the parameter selection strategy from uniform random sampling to entropy-based selective sampling. By dynamically adjusting which input parameters are tested based on their information content (entropy), the system achieves better program generation accuracy with fewer computational iterations
2Reliability
If multiple programs are generated with different transformation contents to improve output accuracy, then the reliability of obtaining correct output data improves, but the complexity of program generation process increases
Solution Approach 1:
The system implements feedback mechanisms where the entropy calculation results from testing one program inform the generation of subsequent programs. The feedback loop uses entropy measurements to guide whether to generate more programs or refine existing ones, reducing unnecessary complexity while maintaining high output correctness
Solution Approach 2:
The program generation process is made dynamic and adaptive rather than static. The system dynamically adjusts the number and type of programs generated based on real-time entropy measurements, creating a flexible process that reduces complexity by avoiding fixed, overly-complex generation protocols
3Reliability
If the PBE regenerates the program multiple times until desired output is obtained, then the reliability of output data improves, but the time required and computational resources increase
Solution Approach 1:
Before full program regeneration, the system performs preliminary entropy-based filtering to identify which input data combinations are most likely to yield desired outputs. This preliminary action reduces the number of full regeneration cycles needed, saving time while maintaining reliability
Solution Approach 2:
The system changes the approach from repeated full program regeneration to targeted parameter adjustment based on entropy analysis. By modifying only the necessary parameters identified through entropy calculation, the system achieves desired outputs faster without sacrificing reliability
Data Source
AI summary
A non-transitory computer-readable recording medium storing a data transformation program that causes a processor to execute a process. The process includes generating a plurality of first programs, each of the first programs transforming first input data and outputting first output data, contents of the transforming by the plurality of the first programs being different from each other, and among a plurality of pieces of a second input data different from the first input data, outputting the second input data that maximizes an entropy of a plurality of pieces of second output data, where each of the first programs transforms the second input data to the second output data.