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Found 5 papers, 2 papers with code
How Much is Unseen Depends Chiefly on Information About the Seen
In our experiments, our genetic algorithm discovers estimators that have a substantially smaller MSE than the state-of-the-art Good-Turing estimator.
Limits of Machine Learning for Automatic Vulnerability Detection
To study this question, researchers proposed to amplify the testing set by injecting semantic preserving changes and found that the model's accuracy significantly drops.
Human-In-The-Loop Automatic Program Repair
Our key challenge is to maximize the oracle's accuracy in predicting which tests are bug-exposing given a small budget of queries.
MCPA: Program Analysis as Machine Learning
The parameters $\delta>0$ and $\epsilon>0$ can be chosen arbitrarily close to zero (0) such that the program analysis outcome is said to be probably-approximately correct (PAC).
Smart Greybox Fuzzing
In this work, we introduce smart greybox fuzzing (SGF) which leverages a high-level structural representation of the seed file to generate new files.
Cryptography and Security
