Refactoring tools, whether fully automated or semi-automated, are essential components of the software development life cycle. As software libraries and frameworks evolve over time, it’s crucial for programs utilizin...Refactoring tools, whether fully automated or semi-automated, are essential components of the software development life cycle. As software libraries and frameworks evolve over time, it’s crucial for programs utilizing them to also evolve to remain compatible with modern advancements. Take, for example, NVIDIA CUDA’s platform for general-purpose GPU programming. Embracing the more contemporary unified memory architecture offers several benefits, such as simplifying program source code, reducing bugs stemming from manual memory management between host and device memory, and optimizing memory transfer through automated memory handling. This paper describes our development of a refactoring tool based on Clang’s Libtooling to facilitate this transition automatically, thereby relieving developers from the burden and risks associated with manually refactoring large code bases.展开更多
A race condition is a common trigger for concurrency bugs. As a special case, a race condition can also occur across the kernel and user space causing a doublefetch bug, which is a field that has received little resea...A race condition is a common trigger for concurrency bugs. As a special case, a race condition can also occur across the kernel and user space causing a doublefetch bug, which is a field that has received little research attention. In our work, we first analyzed real-world doublefetch bug cases and extracted two specific patterns for doublefetch bugs. Based on these patter ns, we proposed an approach of multi-taint parallel tracking to detect double-fetch bugs. We also implemented a prototype called DFTracker (doublefetch bug tracker), and we evaluated it with our test suite. Our experiments demonstrated that it could effectively find all the double-fetch bugs in the test suite including eight realworld cases with no false negatives and minor false positives. In addition, we tested it on Linux kernel and found a new double-fetch bug. The execution overhead is approximately 2x for single-file cases and approximately 9x for the whole kernel test, which is acceptable. To the best of the authors1 knowledge, this work is the first to introduce multi-taint parallel tracking to double-fetch bug detection—an innovative method that is specific to double-fetch bug features—and has better path coverage as well as lower runtime overhead than the widely used dynamic approaches.展开更多
文摘Refactoring tools, whether fully automated or semi-automated, are essential components of the software development life cycle. As software libraries and frameworks evolve over time, it’s crucial for programs utilizing them to also evolve to remain compatible with modern advancements. Take, for example, NVIDIA CUDA’s platform for general-purpose GPU programming. Embracing the more contemporary unified memory architecture offers several benefits, such as simplifying program source code, reducing bugs stemming from manual memory management between host and device memory, and optimizing memory transfer through automated memory handling. This paper describes our development of a refactoring tool based on Clang’s Libtooling to facilitate this transition automatically, thereby relieving developers from the burden and risks associated with manually refactoring large code bases.
文摘A race condition is a common trigger for concurrency bugs. As a special case, a race condition can also occur across the kernel and user space causing a doublefetch bug, which is a field that has received little research attention. In our work, we first analyzed real-world doublefetch bug cases and extracted two specific patterns for doublefetch bugs. Based on these patter ns, we proposed an approach of multi-taint parallel tracking to detect double-fetch bugs. We also implemented a prototype called DFTracker (doublefetch bug tracker), and we evaluated it with our test suite. Our experiments demonstrated that it could effectively find all the double-fetch bugs in the test suite including eight realworld cases with no false negatives and minor false positives. In addition, we tested it on Linux kernel and found a new double-fetch bug. The execution overhead is approximately 2x for single-file cases and approximately 9x for the whole kernel test, which is acceptable. To the best of the authors1 knowledge, this work is the first to introduce multi-taint parallel tracking to double-fetch bug detection—an innovative method that is specific to double-fetch bug features—and has better path coverage as well as lower runtime overhead than the widely used dynamic approaches.
