DOI: 10.5281/zenodo.8025836
title: Dynamic Slicing of WebAssembly Binaries

description: This is the replication package that accompanies the paper titled: "Dynamic Slicing of WebAssembly Binaries". # Slices dataset<br> ## Generating the dataset<br> The dynamic slices have been generated with [P-ORBS](https://syed-islam.github.io/research/program-analysis/#observation-based-program-slicing-orbs).<br> The steps and scripts to generate the dynamic slices are included in the `slicing-steps/` directory.<br> These steps also describe how to generate the `stats.csv` file that is included in this dataset. The static slices have been generated with [wassail](https://github.com/acieroid/wassail).<br> The scripts to generate the static slices are included in the current directory (`generate-static-slices.sh` which relies on `run_wassail.sh`).<br> These steps generate the file `static-stats.csv` that is included in this dataset. The `original-size.csv` file, included in this dataset, can be generated as follows:<br> ```sh<br> find subjects-wasm-extract-slice -name \*.c.wat -exec c_count {} \; | grep subjects &gt; counts.txt<br> echo 'slice,original fn slice' &gt; evaluation/original-sizes.csv<br> sed -E 's|^(.*) subjects-wasm-extract-slice/[^/]*/([^/]*)/.*$|\2,\1|' counts.txt &gt;&gt; evaluation/original-sizes.csv<br> ``` The numbers in Table 1 of the paper (the list of programs in the dataset along with their sizes) can be generated as follows.<br> For the WebAssembly files, we can count the function size: ```<br> find subjects-wasm-extract-slice -name \*.c.wat -exec c_count {} \; | grep subjects &gt; counts.txt<br> sed -E 's|^(.*) subjects-wasm-extract-slice/([^/]*)/.*$|\1 \2|' counts.txt | python evaluation/table1-wasm-mean.py<br> ``` or the full program size: ```<br> find subjects-wasm-extract-slice -name t.wat -exec c_count {} \; | grep subjects &gt; counts.txt<br> sed -E 's|^(.*) subjects-wasm-extract-slice/([^/]*)/.*$|\1 \2|' counts.txt | python evaluation/table1-wasm-mean.py<br> ``` ## Structure of the dataset The dataset is structured as follows: - `subjects/` contains the instrumented `.c` source code, along with scripts to generate the dynamic slices.<br> The original source code can be obtained by removing the line `printf("\nORBS:%x\n....`.<br> - `subjects-wasm-extract-slice/` contains the original WebAssembly programs to slice. Each program has two files: `t.wat` is the full binary file, and `name.c.wat` is the binary code of the function containing the slicing criterion.<br> - `all_slices/` contains the slices. For example, program `adpcm_ah1_254_expr` has the following files<br> - `adpcm/adpcm_ah1_254_expr/EWS_adpcm.wat`: the EWS slice<br> - `adpcm/adpcm_ah1_254_expr/SEW_adpcm.wat`: the SEW slice<br> - `adpcm/adpcm_ah1_254_expr/ESW_adpcm.wat`: the ESW slice<br> - `adpcm/adpcm_ah1_254_expr/static_adpcm.wat.slice`: the SWS slice<br> The other files are produced by intermediary steps and can be ignored. They are:<br> - `adpcm/adpcm_ah1_254_expr/ESW_adpcm.wat.orig`: original (unsliced) binary *file* from which SW and ESW slices are computed<br> - `adpcm/adpcm_ah1_254_expr/SEW_adpcm.wat.orig`: original (unsliced) binary *function* from which SEW slice is computed<br> - `adpcm/adpcm_ah1_254_expr/SW_adpcm.wat`: slice of entire binary file from which ESW slice is extracted<br> - `adpcm/adpcm_ah1_254_expr/WS_adpcm.wat`: compiled (binary) version of dynamic C slice from which EWS slice is extracted<br> <br> # Research questions<br> ## RQ1 The script `./RQ1.py` found in the `evaluation/` directory generates: - Figure 3 (time.pdf)<br> - The mean, min, max, and stddev of the times<br> - How many slices are computed below 10, 100, 1000, and 10000 seconds ## RQ2 The script `./RQ2.py` found in the `evaluation/` directory generates: - Figure 4 (loc.pdf)<br> - The mean, median, min, max, and stddev of the sizes<br> - The largest differences between the approaches<br> - The number of slices larger than the original program<br> <br> ## RQ3 and RQ4 The process for these research questions is manual and requires comparing slices.<br> It cannot be automated. <br> We did make heavy use of `diff --side-by-side` in this analysis.<br>