Efficient Fairness Testing Through Hash-Based Sampling.

There is a growing concern on algorithm fairness, according to wider adoption of machine learning techniques in our daily life. Testing of individual fairness is an approach to algorithm fairness concern. Verification Based Testing (V-BT) is a state-of-the-art testing technique for individual fairness, that leverages verification techniques using constraint solving. In this paper, we develop a black-box individual fairness testing technique V-BT-X, which applies hash-based sampling techniques to the test case generation part of V-BT, aiming to improve its testing ability. Our evaluation by experiments confirms that V-BT-X improves the testing ability of V-BT by 2.92 times in average.