The C11 standard introduced atomic types and operations, with an accompanying memory model, to enable the use of shared variables in concurrent programs. In this thesis, I demonstrate how compilers can be tested, in a way that is deterministic and covers the entire set of atomic operations, to ensure they correctly implement C11 atomics and the C11 memory model.  I use a large set of short concurrent programs (”litmus tests”), generated from a model written in a specification language and based on a formalized C11 memory model. Each test program is compiled and run with a model checker, to determine the possible outcomes; any program with an outcome that is possible after compilation but not allowed by C11 is a failed test case. As an alternative to model checking, I also test a nondeterministic, hardware-based method for running tests, but I find that this method is too inaccurate to be useful.  I test IAR and gcc compilers for Arm and RISC-V; all of these compilers pass all tests. Out of three compilers with purposefully inserted bugs, all are correctly identified as faulty. This testing process thus shows some promise, but further evaluation is needed.

Most software projects today are written using programming languages. Compilers in turn translate programs written in these higher level languages into machine code, executable on actual hardware. Ensuring that these compilers function correctly is therefore paramount. Manually written test suites make sure that compilers functions correctly for some inputs, but can never hope to cover every possible use case. Thus, it is of interest to find out how other testing techniques can be applied. This project aimed to implement a random test program generator for Configura Magic (CM), a proprietary programming language used at Configura. Our tool is inspired by the widely successful C program generator Csmith. It is implemented by randomly generating an abstract syntax tree (AST) and unparsing it to produce correct code. Our tool found about 3 bugs in the CM compiler, Configura Virtual Machine (CVM), during its development.CVM was instrumented to get code coverage data after compiling programs. Compiling the CVM test suite (CTS) and Configura's main product CET (Configura Extension Technology)cover about 23% and 19% of the compiler respectively, while compiling programs generated by our tool only cover about 6%. But on the other hand, our generated programs uniquely cover about 0.2% that is not covered by CTS and CET. A backend for our tool that generates C-code was also implemented, to compare it against Csmith. The results show that on average (100 program generations 30 times, for a total of 3000 programs), our tool gets about 45% coverage while Csmith gets about 50% on the small C compiler TinyCC. Although our tool was mildly successful in finding bugs, the comparison between it and Csmith shows its potential to be even more effective.