Dataset Open Access
Supplemental artifacts of the paper: Efficient Binary-Level Coverage Analysis
M. Ammar Ben Khadra
NOTE: the official repository of bcov is: https://github.com/abenkhadra/bcov
This repository contains the artifacts accompanying our paper: "Efficient Binary-Level Coverage Analysis", which appeared in ESEC/FSE'20. The artifacts consists of two packages, namely, bcov-benchmarks.tar.gz and bcov-artifacts.tar.gz. The former package contains the complete list of binaries described in our experiments. The artifacts of the latter package are organized as follows:
- sample-binaries. Folder that contains sample binaries patched with bcov.
- dataset.tar.gz. Package containing experimental data in csv format.
- figures. Folder that contains the python script used to generate the figures
of our paper. It assumes that the dataset was first extracted to the folder `dataset`.
- install.sh. This script builds and installs bcov together with its dependencies.
- experiment-01.sh. This script patches our sample binaries and shows how coverage
data can be collected. It assumes that bcov was installed using the previous script.
- bcov.tar.gz. Source code of the first public version of `bcov`. The tool is distributed under an MIT license.
| Name | Size | |
|---|---|---|
|
bcov-artifacts.tar.gz
md5:a3d1756d83ef7ee51dc92cdf1e2684c4 |
61.9 MB | Download |
|
bcov-benchmarks.tar.gz
md5:663d4f49ebb5fe8d6f54cfc80c2c2c85 |
1.6 GB | Download |
| All versions | This version | |
|---|---|---|
| Views | 312 | 149 |
| Downloads | 16 | 11 |
| Data volume | 5.5 GB | 5.2 GB |
| Unique views | 262 | 135 |
| Unique downloads | 13 | 8 |
- Publication date:
- January 24, 2021
- DOI:
-
- Keyword(s):
- code coverage analysis, jump table analysis, reverse engineering, static binary instrumentation, supplemental artifacts
- Meeting:
- The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), Virtual Event, USA, Nov, 2020
- Related identifiers:
- Supplement to
- 10.1145/3368089.3409694 (Conference paper)
- License (for files):
- Creative Commons Attribution 4.0 International