TASE: Reducing latency of symbolic execution with transactional memory
This work addresses latency issues in symbolic execution for applications such as client-server verification, representing an incremental improvement through hybrid execution techniques.
The paper tackles the problem of high latency in symbolic execution by introducing TASE, a tool that uses transactional memory to reduce latency for applications with small symbolic state, achieving dramatic improvements in latency-sensitive scenarios like client-server verification.
We present the design and implementation of a tool called TASE that uses transactional memory to reduce the latency of symbolic-execution applications with small amounts of symbolic state. Execution paths are executed natively while operating on concrete values, and only when execution encounters symbolic values (or modeled functions) is native execution suspended and interpretation begun. Execution then returns to its native mode when symbolic values are no longer encountered. The key innovations in the design of TASE are a technique for amortizing the cost of checking whether values are symbolic over few instructions, and the use of hardware-supported transactional memory (TSX) to implement native execution that rolls back with no effect when use of a symbolic value is detected (perhaps belatedly). We show that TASE has the potential to dramatically improve some latency-sensitive applications of symbolic execution, such as methods to verify the behavior of a client in a client-server application.