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In the following, we describe how to build the Docker image and run the experiments in Docker containers.
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In the following, we describe how to replicate the validation from our paper (Section 5) step-by-step.
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The instructions explain how to build the Docker image and run the validation in a Docker container.
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### Install Docker (if required)
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How to install Docker depends on your operating system.
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### 1. Install Docker (if required)
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How to install Docker depends on your operating system:
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#### Windows or Mac
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You can find download and installation instructions [here](https://www.docker.com/get-started).
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#### Linux Distributions
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How to install Docker on your system, depends on your distribution. However, the chances are high that Docker is part of your distributions package database.
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-_Windows or Mac_: You can find download and installation instructions [here](https://www.docker.com/get-started).
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-_Linux Distributions_: How to install Docker on your system, depends on your distribution. The chances are high that Docker is part of your distributions package database.
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Docker's [documentation](https://docs.docker.com/engine/install/) contains instructions for common distributions.
Then, navigate to the root of your local clone of this repository:
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```shell
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cd DiffDetective
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```
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### 3. Build the Docker Container
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To build the Docker container you can run the `build` script corresponding to your operating system:
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```
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# Windows:
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.\build.bat
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# Linux/Mac (bash):
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./build.sh
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```
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## Verification & Expected Output
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## 4. Verification & Replication
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### Running the Replication or Verification
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To execute the replication you can run the `execute` script corresponding to your operating system with `replication` as first argument.
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#### Windows:
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`.\execute.bat replication`
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#### Linux/Mac (bash):
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`./execute.sh replication`
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> WARNING!
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> The replication will at least require an hour and might require up to a day depending on your system.
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> Therefore, we offer a short verification (5-10 minutes) which runs DiffDetective on only four of the datasets.
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> You can run it by providing "verification" as argument instead of "replication" (i.e., `.\execute.bat verification`, `./execute.sh verification`).
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> If you want to stop the execution, you can call the provided script for stopping the container in a separate terminal.
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> When restarted, the execution will continue processing by restarting at the last unfinished repository.
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> #### Windows:
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> `.\stop-execution.bat`
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> #### Linux/Mac (bash):
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> `./stop-execution.sh`
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You might see warnings or errors reported from SLF4J like `Failed to load class "org.slf4j.impl.StaticLoggerBinder"` which you can safely ignore.
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Further troubleshooting advice can be found at the bottom of this file.
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### Running the Verification
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To run the verification you can run the script corresponding to your OS with `verification` as first argument. The verification should take about 10-20 minutes depending on your hardware.
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```
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# Windows:
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.\execute.bat verification
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# Linux/Mac (bash):
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./execute.sh verification
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```
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The results of the verification will be stored in the [results](results) directory.
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### Expected Output of the Verification
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The aggregated results of the verification can be found in the following files.
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The aggregated results of the verification/replication can be found in the following files.
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The example file content shown below should match your results when running the _verification_.
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(Note that the links below only have a target _after_ running the replication or verification.)
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- The [speed statistics](results/validation/speedstatistics.txt) contain information about the total runtime, median runtime, mean runtime, and more:
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- The [speed statistics](results/validation/current/speedstatistics.txt) contain information about the total runtime, median runtime, mean runtime, and more:
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```
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#Commits: 14527
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Total commit process time is: 12.427866666666667min
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Fastest commit process time is: df4a1fa9c5cc5d54a9347a2bf4843cae87a942f1___xorg-server___0ms
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Slowest commit process time is: 9838b7032ea9792bec21af424c53c07078636d21___xorg-server___14578ms
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Median commit process time is: 6dc71f6b2c7ff49adb504426b4cd206e4745e1e3___xorg-server___19ms
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Average commit process time is: 51.330075032697735ms
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#Commits: 24701
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Total commit process time is: 14.065916666666668min
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Fastest commit process time is: d86e352859e797f6792d6013054435ae0538ef6d___xfig___0ms
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Slowest commit process time is: 9838b7032ea9792bec21af424c53c07078636d21___xorg-server___7996ms
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Median commit process time is: f77ffeb9b26f49ef66f77929848f2ac9486f1081___tcl___13ms
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Average commit process time is: 34.166835350795516ms
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```
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- The [classification results](results/validation/ultimateresult.metadata.txt) contain information about how often each pattern was found, and more.
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- The [classification results](results/validation/current/ultimateresult.metadata.txt) contain information about how often each pattern was matched, and more.
edgeformat: org.variantsync.diffdetective.mining.formats.DirectedEdgeLabelFormat with org.variantsync.diffdetective.mining.formats.ReleaseMiningDiffNodeFormat
(Note that the above links only have a target after running the verification.)
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The processing times might deviate.
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Moreover, the results comprise the (LaTeX) tables that are part of our paper and appendix.
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The processing times might deviate because performance depends on your hardware.
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### (Optional) Running DiffDetective on Custom Datasets
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You can also run DiffDetective on other datasets by providing the path to the dataset file as first argument to the execution script:
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#### Windows:
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`.\execute.bat path\to\custom\dataset.md`
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#### Linux/Mac (bash):
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`./execute.sh path/to/custom/dataset.md`
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The input file must have the same format as the other dataset files (i.e., repositories are listed in a Markdown table). You can find [dataset files](docs/datasets.md) in the [docs](docs) folder.
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## Troubleshooting
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### 'Got permission denied while trying to connect to the Docker daemon socket'
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`Problem:` This is a common problem under Linux, if the user trying to execute Docker commands does not have the permissions to do so.
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`Fix:` You can fix this problem by either following the [post-installation instructions](https://docs.docker.com/engine/install/linux-postinstall/), or by executing the scripts in the replication package with elevated permissions (i.e., `sudo`)
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`Fix:` You can fix this problem by either following the [post-installation instructions](https://docs.docker.com/engine/install/linux-postinstall/), or by executing the scripts in the replication package with elevated permissions (i.e., `sudo`).
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### 'Unable to find image 'replication-package:latest' locally'
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`Problem:` The Docker container could not be found. This either means that the name of the container that was built does not fit the name of the container that is being executed (this only happens if you changed the provided scripts), or that the Docker container was not built yet.
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`Fix:` Follow the instructions described above in the section `Build the Docker Container`.
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### No results after verification, or 'cannot create directory '../results/difftrees': Permission denied'
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### No results after verification, or 'cannot create directory '../results/validation/current': Permission denied'
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`Problem:` This problem can occur due to how permissions are managed inside the Docker container. More specifically, it will appear, if Docker is executed with elevated permissions (i.e., `sudo`) and if there is no [results](results) directory because it was deleted manually. In this case, Docker will create the directory with elevated permissions, and the Docker user has no permissions to access the directory.
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`Fix:` If there is a _results_ directory delete it with elevated permission (e.g., `sudo rm -r results`).
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`Fix:` If there is a _results_ directory, delete it with elevated permission (e.g., `sudo rm -r results`).
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Then, create a new _results_ directory without elevated permissions, or execute `git restore .` to restore the deleted directory.
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### Failed to load class "org.slf4j.impl.StaticLoggerBinder"
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`Problem:` An operation within the initialization phase of the logger library we use (tinylog) failed.
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`Fix:` Please ignore this warning. Tinylog will fall back onto a default implementation (`Defaulting to no-operation (NOP) logger implementation`) and logging will work as expected.
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