APT Detection with Concolic Execution

Concolic Execution for Django Applications

Concolic execution systems allow developers to verify that invariants in their applications are not violated no matter what input is given by a user. This was demonstrated in Lab 3, where the Z3 solver was used to find inputs that would trigger inconsistencies in Zoobar balances. Unfortunately, the lab’s framework is written specifically for Zoobar, and would therefore not work for other applic...

Multi-trace Concolic Execution Framework

Oasis: Concolic Execution Driven by Test Suites and Code Modifications

Testing remains an important aspect of checking software correctness. Manually constructed test suites are one option: they typically complete quickly, but they require human involvement in producing test cases, and their coverage may be limited. Recently, symbolic execution and concolic execution have been investigated as alternatives to test suites. These approaches require little manual inte...

Concolic Execution in Functional Programming by Program Instrumentation

Concolic execution, a combination of concrete and symbolic execution, has become increasingly popular in recent approaches to model checking and test case generation. In general, an interpreter of the language is augmented in order to also deal with symbolic values. In this paper, in contrast, we present a lightweight approach that is based on a program instrumentation. Basically, the execution...

Concolic Execution and Test Case Generation in Prolog

Symbolic execution extends concrete execution by allowing symbolic input data and then exploring all feasible execution paths. It has been defined and used in the context of many different programming languages and paradigms. A symbolic execution engine is at the heart of many program analysis and transformation techniques, like partial evaluation, test case generation or model checking, to nam...