| Summary: | Software is large, complex, and error-prone. According to the US National Institute of Standards and Technology, software bugs cost the US economy an estimated $60 billion each year. The trend in hardware design of switching to multi-core architectures makes software development even more complex. Cutting software development costs and ensuring higher reliability of software is of global interest and a grand challenge. This is especially true of the system software that is the foundation beneath all general-purpose application programs.
The verification of system software poses particular challenges: system software is typically written in a low-level programming language with dynamic memory allocation and pointer manipulation, and system software is also highly concurrent, with shared-memory communication being the main concurrent programming paradigm. Available verification tools usually perform poorly when dealing with the aforementioned challenges. This thesis addresses these problems by enabling precise and scalable verification of low-level, shared-memory, concurrent programs. The main contributions are about the interrelated concepts of memory, modularity, and concurrency.
First, because programs use huge amounts of memory, the memory is usually modeled very imprecisely in order to scale to big programs. This imprecise modeling renders most tools almost useless in the memory-intensive parts of code. This thesis describes a scalable, yet precise, memory model that offers on-demand precision only when necessary.
Second, modularity is the key to scalability, but it often comes with a price --- a user must manually provide module specifications, making the verification process more tedious. This thesis proposes a light-weight technique for automatically inferring an important family of specifications to make the verification process more automatic.
Third, the number of program behaviors explodes in the presence of concurrency, thereby greatly increasing the complexity of the verification task. This explosion is especially true of shared-memory concurrency. The thesis presents a static context-bounded analysis that combines a number of techniques to successfully solve this problem.
We have implemented the above contributions in the verification tools developed as a part of this thesis. We have applied the tools on real-life system software, and we are already finding critical, previously undiscovered bugs. === Science, Faculty of === Computer Science, Department of === Graduate
|
|---|
