Graph matching is a fundamental problem in pattern recognition, with many applications such as software analysis and computational biology. One well-known type of graph matching problem is graph isomorphism, which consists of deciding if two graphs are identical. Despite its usefulness, the properties that one may check using graph isomorphism are rather limited, since it only allows strict equality checks between two graphs. For example, it does not allow one to check complex structural properties such as if the target graph is an arbitrary length sequence followed by an arbitrary size loop. We propose a generalization of graph isomorphism that allows one to check such properties through a declarative specification. This specification is given in the form of a Regular Graph Pattern (ReGaP), a special type of graph, inspired by regular expressions, that may contain wildcard nodes that represent arbitrary structures such as variable-sized sequences or subgraphs. We propose a SAT-based algorithm for checking if a target graph matches a given ReGaP. We also propose a preprocessing technique for improving the performance of the algorithm and evaluate it through an extensive experimental evaluation on benchmarks from the CodeSearchNet dataset.

Low-code platforms enable rapid development of complex mission critical software applications. Nevertheless, these applications still must adhere to software principles. In particular, the developers need to create tests as part of their development cycle. However, this process involves significant effort from manual testing to manually coding tests. This process can be time-consuming and error-prone, especially for large and complex applications. In this paper, we propose using symbolic execution to generate tests for low-code applications. Symbolic execution is a technique that allows the exploration of all possible paths of a program, without requiring it to be executed with concrete values. Although symbolic execution has scalability issues due to path explosion, we mitigate the problem by exploring the properties of the low-code framework. We evaluate our approach using a set of real-world low-code applications and compare it to equivalent testing techniques for text-based programming languages. Our results show that symbolic execution can produce high quality results in a short amount of time when applied to visual programming languages. We believe that our approach has the potential to improve the quality and reliability of low-code applications while reducing the time and effort required for testing.