A system to flag anomalous source code expressions by learning typical expressions from training data

A system to flag anomalous source code expressions by learning typical expressions from training data

GitHub – IntelLabs/control-flag: A system to flag anomalous source code expressions by learning typical expressions from training data

“ControlFlag’s pattern anomaly detection system can be used for various problems such as typographical error detection, flagging a missing NULL check to name a few. This PoC demonstrates ControlFlag’s application in the typographical error detection.

Figure below shows ControlFlag’s two main phases: (1) pattern mining phase, and (2) scanning for anomalous patterns phase. The pattern mining phase is a “training phase” that mines typical patterns in the user-provided GitHub repositories and then builds a decision-tree from the mined patterns. The scanning phase, on the other hand, applies the mined patterns to flag anomalous expressions in the user-specified target repositories…”

Source: github.com/IntelLabs/control-flag