A review of 42 primary studies expands the definition of Algorithm Debt in ML/DL systems, identifies its smells, and suggests future research directions.
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An empirical evaluation found that HECATE generated failure-revealing test cases for 83% of 36 experiments on e-bike Simulink controllers, averaging 1 hour 17 minutes per run, with developer confirmation of the failures.
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A Survey of Algorithm Debt in Machine and Deep Learning Systems: Definition, Smells, and Future Work
A review of 42 primary studies expands the definition of Algorithm Debt in ML/DL systems, identifies its smells, and suggests future research directions.
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Test Case Generation for Simulink Models: An Experience from the E-Bike Domain
An empirical evaluation found that HECATE generated failure-revealing test cases for 83% of 36 experiments on e-bike Simulink controllers, averaging 1 hour 17 minutes per run, with developer confirmation of the failures.