A Symbolic Execution Algorithm for Constraint-Based Testing of Database Programs

TL;DR

This paper introduces a symbolic execution algorithm tailored for constraint-based testing of database programs, using a formal language to model interactions and generating test data that guarantees path coverage.

Contribution

It proposes a novel symbolic execution algorithm for SimpleDB, a formal language for database-program interactions, enabling systematic test data generation for database-involving programs.

Findings

Algorithm effectively generates test inputs for database programs.

Experimental evaluation shows promising results on SimpleDB models.

Ensures path-specific testing with database state initialization.

Abstract

In so-called constraint-based testing, symbolic execution is a common technique used as a part of the process to generate test data for imperative programs. Databases are ubiquitous in software and testing of programs manipulating databases is thus essential to enhance the reliability of software. This work proposes and evaluates experimentally a symbolic ex- ecution algorithm for constraint-based testing of database programs. First, we describe SimpleDB, a formal language which offers a minimal and well-defined syntax and seman- tics, to model common interaction scenarios between pro- grams and databases. Secondly, we detail the proposed al- gorithm for symbolic execution of SimpleDB models. This algorithm considers a SimpleDB program as a sequence of operations over a set of relational variables, modeling both the database tables and the program variables. By inte- grating this relational model of the program with classical static symbolic execution, the algorithm can generate a set of path constraints for any finite path to test in the control- flow graph of the program. Solutions of these constraints are test inputs for the program, including an initial content for the database. When the program is executed with respect to these inputs, it is guaranteed to follow the path with re- spect to which the constraints were generated. Finally, the algorithm is evaluated experimentally using representative SimpleDB models.