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‎.run/GenAutomationResults.run.xml‎

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<component name="ProjectRunConfigurationManager">
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<configuration default="false" name="GenAutomationResults" type="Application" factoryName="Application">
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<option name="MAIN_CLASS_NAME" value="org.variantsync.diffdetective.main.FindMedianCommitTime" />
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<option name="MAIN_CLASS_NAME" value="org.variantsync.diffdetective.validation.FindMedianCommitTime" />
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<module name="DiffDetective" />
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<option name="PROGRAM_PARAMETERS" value="results/difftrees" />
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<extension name="coverage">

‎.run/Generate Javadoc.run.xml‎

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<component name="ProjectRunConfigurationManager">
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<configuration default="false" name="Generate Javadoc" type="MavenRunConfiguration" factoryName="Maven">
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<MavenSettings>
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<option name="myGeneralSettings" />
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<option name="myRunnerSettings" />
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<option name="myRunnerParameters">
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<MavenRunnerParameters>
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<option name="profiles">
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<set />
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</option>
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<option name="goals">
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<list>
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<option value="javadoc:javadoc" />
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</list>
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</option>
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<option name="pomFileName" />
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<option name="profilesMap">
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<map />
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</option>
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<option name="resolveToWorkspace" value="false" />
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<option name="workingDirPath" value="$PROJECT_DIR$" />
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</MavenRunnerParameters>
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</option>
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</MavenSettings>
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<method v="2" />
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</configuration>
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</component>

‎LICENSE.LGPL3‎

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GNU LESSER GENERAL PUBLIC LICENSE
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Version 3, 29 June 2007
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Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
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Everyone is permitted to copy and distribute verbatim copies
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of this license document, but changing it is not allowed.
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This version of the GNU Lesser General Public License incorporates
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the terms and conditions of version 3 of the GNU General Public
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License, supplemented by the additional permissions listed below.
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0. Additional Definitions.
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General Public License, and the "GNU GPL" refers to version 3 of the GNU
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‎README.md‎

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This replication package consists of four parts:
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1. **Appendix**: The appendix of our paper is given in PDF format in the file [appendix.pdf](appendix.pdf).
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2. **DiffDetective**: For our validation, we built DiffDetective, a java library and command-line tool to classify edits to variability in git histories of preprocessor-based software product lines.
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1. **DiffDetective**: For our validation, we built DiffDetective, a java library and command-line tool to classify edits to variability in git histories of preprocessor-based software product lines.
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2. **Appendix**: The appendix of our paper is given in PDF format in the file [appendix.pdf](appendix.pdf).
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3. **Haskell Formalization**: We provide an extended formalization in the Haskell programming language as described in our appendix. Its implementation can be found in the Haskell project in the [proofs](proofs) directory.
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4. **Dataset Overview**: We provide an overview of the 44 inspected datasets with updated links to their repositories in the file [docs/datasets.md](docs/datasets.md).
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4. **Dataset Overview**: We provide an overview of the 44 inspected datasets with updated links to their repositories in the file [docs/datasets.md][dataset].
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## Appendix
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Our appendix consists of:
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1. An extended formalization of our concepts in the [Haskell][haskell] programming language. The corresponding source code is also part of this replication package (see below).
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2. The proofs for (a) the completeness of variation tree diffs to represent edits to variation trees, and (b) the completeness and unambiguity of our elementary edit patterns.
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3. An inspection of edit patterns from related work to show that existing patterns are either composite patterns built from our elementary patterns or similar to our elementary patterns.
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4. The complete results of our validation for all 44 datasets.
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## DiffDetective
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## 1. DiffDetective
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We offer a [Docker](https://www.docker.com/) setup to easily __replicate__ our validation with _DiffDetective_.
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You can find detailed information on how to install Docker and build the container in the [INSTALL](INSTALL.md) file.
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In the following, we provide instructions for running the replication.
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### 2. Start the replication
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To execute the replication you can run the _execute_ script corresponding to your OS with `replication` as first argument.
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> ! The replication will at least require several hours and might require up to a few days depending on your system.
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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 validation (5-10 minutes) which runs _DiffDetective_ on only four of the datasets.
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> You can run it by providing "validation" as argument instead of "replication" (i.e., ./execute.sh validation).
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> If you want to stop the replication, you can call the provided script for stopping the container. Note that you will have to restart the entire replication, if you stop it at any point.
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#### Linux/Mac (bash):
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`./execute.sh replication`
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### 3. View the results in the [results](results) directory
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All raw results are stored in the [results](results) directory. The aggregated results can be found in the following files:
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- [speed statistics](results/difftrees/speedstatistics.txt): contains information about the total runtime, median runtime, mean runtime, and more.
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Moreover, the results comprise the (LaTeX) tables that are part of our paper and appendix.
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## Haskell Formalization
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The extended formalization in Haskell is a library using the _Stack_ build system.
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## 2. Appendix
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Our appendix consists of:
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1. An extended formalization of our concepts in the [Haskell][haskell] programming language. The corresponding source code is also part of this replication package (see below).
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2. The proofs for (a) the completeness of variation tree diffs to represent edits to variation trees, and (b) the completeness and unambiguity of our elementary edit patterns.
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3. An inspection of edit patterns from related work to show that existing patterns are either composite patterns built from our elementary patterns or similar to our elementary patterns.
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4. The complete results of our validation for all 44 datasets.
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## 3. Haskell Formalization
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The extended formalization is a [Haskell][haskell] library in the [`proofs`](proofs) subdirectory.
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Since the `proofs` library is its own software project, we provide a separate documentation of requirements and installation instructions within the projects subdirectory.
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Instructions for manually installing Stack are given in [proofs/REQUIREMENTS.md](proofs/REQUIREMENTS.md).
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How to build our library and how to run the example is described in the [proofs/INSTALL.md](proofs/INSTALL.md).
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## 4. Dataset Overview
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We provide an overview of the used 44 open-source preprocessor-based software product lines in the [docs/datasets.md][dataset] file.
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As described in our paper in Section 5.1 this list contains all systems that were studied by Liebig et al., extended by four new subject systems.
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We provide updated links for each system's repository.
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[haskell]: https://www.haskell.org/
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[dataset]: docs/datasets.md

‎REQUIREMENTS.md‎

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## Hardware Requirements
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None
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## Software Requirements
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We do not require a certain operating system or prepared environment.
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We tested our replication on Windows 10, WSL2, and Linux.
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To run DiffDetective, JDK16 and Maven are required.
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Dependencies to other packages are documented in the maven build file ([pom.xml](pom.xml)) and are handled automatically by Maven.
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Alternatively, the docker container can be used on any system supporting docker.
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Docker will take care of all requirements and dependencies to replicate our validation.
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The requirements to build our `proofs` Haskell library are documented in its respective [proofs/REQUIREMENTS.md](proofs/REQUIREMENTS.md) file.
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[stack]: https://docs.haskellstack.org/en/stable/README/

‎STATUS.md‎

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The artifact for the paper _Classifying Edits to Variability in Source Code_ consists of four parts:
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1. **Appendix**: The appendix of our paper is given in PDF format in the file [`appendix.pdf`][ddappendix].
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2. **DiffDetective**: For our validation, we built DiffDetective, a java library and command-line tool to classify edits to variability in git histories of preprocessor-based software product lines. DiffDetective is the main artifact used to replicate the validation for our paper (see Section 5).
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3. **Haskell Formalization**: We provide an extended formalization in the Haskell programming language as described in our appendix. Its implementation can be found in the Haskell project in the [`proofs`][ddproofs] directory.
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4. **Dataset Overview**: We provide an overview of the 44 inspected open-source software product lines with updated links to their repositories in the file [docs/datasets.md](docs/datasets.md).
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Our artifact has the following purposes:
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- **Replicability**: We provide instructions based on a docker container that allow to reproduce the validation we performed in Section 5 of our paper.
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- **Reusability**: DiffDetective is designed as a library that offers reusable functionality.
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Researchers and practitioners can use our DiffDetective library to build on our theory and results (e.g., for future prototypes to study the evolution of variability in source code).
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DiffDetective offers various features, including but not limited to parsing variation tree diffs from unix diffs, obtaining variation tree diffs for certain patches and commits, matching elementary edit patterns on variation tree diffs, defining custom classifications, rendering, traversing, and transformations of variation tree diffs, various de-/serialization methods, and running analyses for the git histories of C preprocessor-based software product lines. We documented each part of the library and provide a javadoc website within the repository.
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- **Extended Formal Specification**: The `proofs` Haskell project provides an extended formal specification of our theory.
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Its main purpose is to document our theory and its extensions and to serve as a reference for the proofs in our appendix.
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The project can also be used as a library to reason on variation trees and diffs in Haskell projects.
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The library is accompanied with a small demo application that shows an example test case for our proof for completeness, by creating a variation tree diff from two variation trees and re-projecting them.
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We claim the **_Artifacts Available_** badge as we made our artefacts publicly available on [Github][ddgithub] and [Zenodo][ddzenodo]. (For now, the Zenodo link points to a reserved doi under which we will publish the artifacts once completed until the deadline at June 4.)
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We claim the **_Artifacts Evaluated Reusable_** badge as we implemented DiffDetective as a reusable library (see above).
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Furthermore, both DiffDetective and our Haskell formalization serve as reference implementations if researchers or practitioners want to reimplement our theory in another programming language.
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[ddgithub]: UNDEFINED
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[ddzenodo]: UNDEFINED
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[ddappendix]: UNDEFINED
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[ddproofs]: UNDEFINED

‎proofs/REQUIREMENTS.md‎

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We do not require specific operating systems or other environments apart from Stack.
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We successfully tested building the library and running the library on Windows 10 and in WSL2.
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[stack]: https://docs.haskellstack.org/en/stable/README/
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[stack]: https://docs.haskellstack.org/en/stable/README/

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