Software and Computational Systems Lab

CPAchecker has several different implementations of pointer-aliasing analyses, and the current state of what they support is unclear. This leads to the fact that they are rarely used and causes wrong results in case of pointer aliasing. The goal of this thesis is to create a strong CPA for pointer aliasing (either by merging the existing CPAs or rewriting them) that supports all necessary use cases (fast and imprecise as well as more precise) and migrate all existing uses of other pointer CPAs, such that the old code can be deleted (#358). Afterwards, it may be possible to add additional features (e.g., #742) or extend other components of CPAchecker to make use of the new CPA (e.g., #527, #398).

This proposal aims to support some significant feature requests for the HTML table component of BenchExec and refactor the code to improve readability and maintainability. These issues include upgrading React Router to the latest stable version 6, merging the two tables on the Summary page to one simple table, displaying the error counts in the table summary, and reworking the filtering logic. Some additional goals are supporting syntax highlighting in overlay panes, adding an intuitive display for command line options in merged runset, and changing the name of the runsets to be more user-friendly.

BenchExec's tests are currently written using the test framework nose, which is not maintained anymore and has problems on new Python versions. The goal of this project is to switch the test framework used for BenchExec. As a first step, an appropriate framework needs to be chosen. This should be done systematically based on criteria like ease of use, how common the framework is, whether it is well maintained etc. Next, the framework needs to be integrated in BenchExec's project structure and the existing tests need to adjusted where necessary. This might also include restructuring the tests and in general improving their state. Filling gaps in our test coverage with more unit tests would also be highly welcome.

CPAchecker produces as result a report about its verification work. An example can be seen here. This report is a web application based on AngularJS and D3. The goal of this project is to replace AngularJS with Angular and to write tests for the functionality of this report using an appropriate framework for automated tests.

If several benchmarking runs should be executed in parallel on the same system, the memory usage of one run can influence the performance of others (because CPU caches and the memory bandwidth is shared), even if each run gets its own reserved share of the memory. Recent Intel CPUs have a cache allocation technology, which allows to control the usage of caches and memory bandwidth and reduce the influence that parallel benchmarking runs have on each other. The goal of this project is to add support for using this technology to BenchExec.

For benchmarking purposes, BenchExec typically creates a container with a file-system overlay atop the system's file system. However, due to a kernel change, this process is no longer viable for the root file system. Implementing fuse-overlayfs as an alternative overlay mechanism might resolve this issue. This entails developing a fallback mechanism for BenchExec's file-system overlay strategy: initially attempting to utilize the kernel overlayfs, and if unsuccessful, resorting to fuse-overlayfs. This approach ensures BenchExec's functionality remains intact.

A study should be conducted that evaluates options for garbage collectors when executing CPAchecker as described in the linked issue. The goal of this thesis is to have usable suggestions on what garbage collectors CPAchecker should use in which situation. For this it is crucial that the study is performed in a systematic and well-planned manner such that the results are reliable and meaningful.

BenchExec is a benchmarking framework and assigns a specific set of CPU cores to each benchmark run. The calculation which core to use for which run needs to consider low-level details of the hardware architecture (like hyper threading, NUMA, etc.) in order to avoid interference between runs as far as possible. Our current implementation supports multi-CPU systems with NUMA and hyper threading, but not some more recent features like hybrid-architecture CPUs or CPUs with split Level 3 caches. The goal of this thesis is to implement a more general core allocation (in Python) with support for all kinds of modern CPUs and additional features and rigorous tests. There should also be an experimental evaluation on how different allocation strategies and such hardware details influence benchmarking results.

Our benchmarking framework BenchExec uses cgroups in order to limit and measure time and memory usage during benchmarking. The Linux kernel is replacing cgroups with a new API (v2) and we need to support this in BenchExec (#133). Once we have it, we can use cgroup namespaces to better isolate our containers and provide full support for nested containers (#436).