Voting Machine Test Decks for Transposition Error Detection
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Solution Overview
Problem
Current electronic voting systems are vulnerable to transposition errors, where candidates' positions on ballots are switched unintentionally or intentionally, leading to undetected errors across different contests, and existing test decks fail to reliably catch these errors.
Innovation Solution
A method and system for constructing a test deck using iterative algorithms to generate a minimum test deck that can defeat all possible transposition 'attack codes', reducing computational resources and run time, and ensuring detection of all transposition errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional test decks are used to check voting systems, then the testing process is simple to implement, but transposition errors across different contests are not reliably detected
Solution Approach 1:
The system performs preliminary analysis of the ballot structure, contests, and candidates before generating the test deck. This advance preparation allows the test deck to be specifically tailored to detect transposition errors across different contests, rather than using generic test ballots. The preliminary action includes parsing the ballot XML structure and identifying all candidate-position relationships.
Solution Approach 2:
The system introduces an intermediary computational process that generates attack codes representing potential transposition errors. These attack codes serve as intermediaries between the ballot structure analysis and the actual test deck generation. The attack codes model various transposition scenarios (within-contest and across-contest) and guide the construction of test ballots that will detect these errors.
2Measurement precision
If comprehensive test decks are generated to cover all possible transposition errors, then detection accuracy improves, but computational time and resources increase
Solution Approach 1:
The system segments the transposition error detection problem into two distinct types: within-contest transpositions and across-contest transpositions. Each segment is handled with specialized attack code generation and test ballot construction strategies. This segmentation allows the system to comprehensively cover all error types without generating redundant test cases, thereby reducing overall computational time while maintaining high detection accuracy.
Solution Approach 2:
The system dynamically adjusts parameters such as the number of test ballots per contest and the complexity of attack codes based on the specific election structure. For elections with fewer candidates or simpler contest structures, the system generates fewer test ballots, reducing computational time. The parameter changes are guided by the parsed ballot structure and the identified transposition risk profiles.
Data Source
AI summary
A transposition error may occur in a voting machine when the voting machine switches candidates so that votes are counted for a different candidates than a voter intended. Such transposition errors may occur due to either intentional manipulation (e.g., a bad actor hacking the voting system, etc.), or unintentional human error (e.g., an unintentional human error in computer programming, etc.). In some embodiments, a “minimum test deck” is created that includes the minimum number of filled out ballots that will effectively test a voting machine to ensure that no transposition error occurred.