[![flowR logo](https://raw.githubusercontent.com/wiki/flowr-analysis/flowr/img/flowR.png)](https://github.com/flowr-analysis/flowr/wiki)\ [![QA (and potentially deploy)](https://github.com/flowr-analysis/flowr/actions/workflows/qa.yaml/badge.svg)](https://github.com/flowr-analysis/flowr/actions/workflows/qa.yaml) [![codecov](https://codecov.io/gh/flowr-analysis/flowr/graph/badge.svg)](https://codecov.io/gh/flowr-analysis/flowr) [![Docker Image Version (latest semver)](https://img.shields.io/docker/v/eagleoutice/flowr?logo=docker&logoColor=white&label=dockerhub)](https://hub.docker.com/r/eagleoutice/flowr) [![latest tag](https://badgen.net/github/tag/flowr-analysis/flowr?label=latest&color=purple)](https://github.com/flowr-analysis/flowr/releases/latest) [![Marketplace](https://badgen.net/vs-marketplace/v/code-inspect.vscode-flowr)](https://marketplace.visualstudio.com/items?itemName=code-inspect.vscode-flowr) [![Marketplace](https://badgen.net/open-vsx/version/code-inspect/vscode-flowr?label=Positron/Open%20VSX)](https://open-vsx.org/extension/code-inspect/vscode-flowr) [![DOI](https://zenodo.org/badge/624819038.svg)](https://zenodo.org/doi/10.5281/zenodo.13319290) _flowR_ is a sophisticated, static [dataflow analyzer](https://en.wikipedia.org/wiki/Data-flow_analysis) for the [R programming language](https://www.r-project.org/), available for [VSCode](https://marketplace.visualstudio.com/items?itemName=code-inspect.vscode-flowr), [Positron](https://open-vsx.org/extension/code-inspect/vscode-flowr), [RStudio](https://github.com/flowr-analysis/rstudio-addin-flowr), and [Docker](https://hub.docker.com/r/eagleoutice/flowr). It offers a wide variety of features, for example: * 🐞 **code linting**\ Analyze your R scripts for common issues and potential bugs (see the [wiki page](https://github.com/flowr-analysis/flowr/wiki/Linter) for more information on the currently supported linters).
Example: Linting code with flowR To lint your code, you can use the [REPL](https://github.com/flowr-analysis/flowr/wiki/Interface#using-the-repl) or the [Visual Studio Code extension](https://marketplace.visualstudio.com/items?itemName=code-inspect.vscode-flowr) (see [vscode-flowr#283](https://github.com/flowr-analysis/vscode-flowr/pull/283)). ```shell $ docker run -it --rm eagleoutice/flowr # or npm run flowr flowR repl using flowR v2.4.6, R v4.5.0 (r-shell engine) R> :query @linter "read.csv(\"/root/x.txt\")" ```
Output ```text Query: linter (2 ms) ╰ **Deprecated Functions** (deprecated-functions): ╰ _Metadata_: {"totalDeprecatedCalls":0,"totalDeprecatedFunctionDefinitions":0,"searchTimeMs":0,"processTimeMs":0} ╰ **File Path Validity** (file-path-validity): ╰ certain: ╰ Path `/root/x.txt` at 1.1-23 ╰ _Metadata_: {"totalReads":1,"totalUnknown":0,"totalWritesBeforeAlways":0,"totalValid":0,"searchTimeMs":1,"processTimeMs":0} ╰ **Seeded Randomness** (seeded-randomness): ╰ _Metadata_: {"consumerCalls":0,"callsWithFunctionProducers":0,"callsWithAssignmentProducers":0,"callsWithNonConstantProducers":0,"searchTimeMs":0,"processTimeMs":0} ╰ **Absolute Paths** (absolute-file-paths): ╰ certain: ╰ Path `/root/x.txt` at 1.1-23 ╰ _Metadata_: {"totalConsidered":1,"totalUnknown":0,"searchTimeMs":0,"processTimeMs":0} ╰ **Unused Definitions** (unused-definitions): ╰ _Metadata_: {"totalConsidered":0,"searchTimeMs":0,"processTimeMs":0} ╰ **Naming Convention** (naming-convention): ╰ _Metadata_: {"numMatches":0,"numBreak":0,"searchTimeMs":0,"processTimeMs":0} ╰ **Dataframe Access Validation** (dataframe-access-validation): ╰ _Metadata_: {"numOperations":0,"numAccesses":0,"totalAccessed":0,"searchTimeMs":0,"processTimeMs":1} ╰ **Dead Code** (dead-code): ╰ _Metadata_: {"consideredNodes":5,"searchTimeMs":0,"processTimeMs":0} ╰ **Useless Loops** (useless-loop): ╰ _Metadata_: {"numOfUselessLoops":0,"searchTimeMs":0,"processTimeMs":0} All queries together required ≈2 ms (1ms accuracy, total 8 ms) ``` The linter will analyze the code and return any issues found. Formatted more nicely, this returns: ```json [ { "type": "linter" } ] ``` (This query can be shortened to `@linter` when used within the REPL command `:query`). _Results (prettified and summarized):_ Query: **linter** (13 ms)\    ╰ **Deprecated Functions** (deprecated-functions):\        ╰ _Metadata_: {"totalDeprecatedCalls":0,"totalDeprecatedFunctionDefinitions":0,"searchTimeMs":2,"processTimeMs":0}\    ╰ **File Path Validity** (file-path-validity):\        ╰ certain:\            ╰ Path `/root/x.txt` at 1.1-23\        ╰ _Metadata_: {"totalReads":1,"totalUnknown":0,"totalWritesBeforeAlways":0,"totalValid":0,"searchTimeMs":4,"processTimeMs":1}\    ╰ **Seeded Randomness** (seeded-randomness):\        ╰ _Metadata_: {"consumerCalls":0,"callsWithFunctionProducers":0,"callsWithAssignmentProducers":0,"callsWithNonConstantProducers":0,"searchTimeMs":0,"processTimeMs":0}\    ╰ **Absolute Paths** (absolute-file-paths):\        ╰ certain:\            ╰ Path `/root/x.txt` at 1.1-23\        ╰ _Metadata_: {"totalConsidered":1,"totalUnknown":0,"searchTimeMs":2,"processTimeMs":0}\    ╰ **Unused Definitions** (unused-definitions):\        ╰ _Metadata_: {"totalConsidered":0,"searchTimeMs":0,"processTimeMs":1}\    ╰ **Naming Convention** (naming-convention):\        ╰ _Metadata_: {"numMatches":0,"numBreak":0,"searchTimeMs":0,"processTimeMs":0}\    ╰ **Dataframe Access Validation** (dataframe-access-validation):\        ╰ _Metadata_: {"numOperations":0,"numAccesses":0,"totalAccessed":0,"searchTimeMs":0,"processTimeMs":2}\    ╰ **Dead Code** (dead-code):\        ╰ _Metadata_: {"consideredNodes":5,"searchTimeMs":1,"processTimeMs":0}\    ╰ **Useless Loops** (useless-loop):\        ╰ _Metadata_: {"numOfUselessLoops":0,"searchTimeMs":0,"processTimeMs":0}\ _All queries together required ≈13 ms (1ms accuracy, total 210 ms)_
Show Detailed Results as Json The analysis required _210.1 ms_ (including parsing and normalization and the query) within the generation environment. In general, the JSON contains the Ids of the nodes in question as they are present in the normalized AST or the dataflow graph of flowR. Please consult the [Interface](https://github.com/flowr-analysis/flowr/wiki/Interface) wiki page for more information on how to get those. ```json { "linter": { "results": { "deprecated-functions": { "results": [], ".meta": { "totalDeprecatedCalls": 0, "totalDeprecatedFunctionDefinitions": 0, "searchTimeMs": 2, "processTimeMs": 0 } }, "file-path-validity": { "results": [ { "range": [ 1, 1, 1, 23 ], "filePath": "/root/x.txt", "certainty": "certain" } ], ".meta": { "totalReads": 1, "totalUnknown": 0, "totalWritesBeforeAlways": 0, "totalValid": 0, "searchTimeMs": 4, "processTimeMs": 1 } }, "seeded-randomness": { "results": [], ".meta": { "consumerCalls": 0, "callsWithFunctionProducers": 0, "callsWithAssignmentProducers": 0, "callsWithNonConstantProducers": 0, "searchTimeMs": 0, "processTimeMs": 0 } }, "absolute-file-paths": { "results": [ { "certainty": "certain", "filePath": "/root/x.txt", "range": [ 1, 1, 1, 23 ] } ], ".meta": { "totalConsidered": 1, "totalUnknown": 0, "searchTimeMs": 2, "processTimeMs": 0 } }, "unused-definitions": { "results": [], ".meta": { "totalConsidered": 0, "searchTimeMs": 0, "processTimeMs": 1 } }, "naming-convention": { "results": [], ".meta": { "numMatches": 0, "numBreak": 0, "searchTimeMs": 0, "processTimeMs": 0 } }, "dataframe-access-validation": { "results": [], ".meta": { "numOperations": 0, "numAccesses": 0, "totalAccessed": 0, "searchTimeMs": 0, "processTimeMs": 2 } }, "dead-code": { "results": [], ".meta": { "consideredNodes": 5, "searchTimeMs": 1, "processTimeMs": 0 } }, "useless-loop": { "results": [], ".meta": { "numOfUselessLoops": 0, "searchTimeMs": 0, "processTimeMs": 0 } } }, ".meta": { "timing": 13 } }, ".meta": { "timing": 13 } } ```
* 🍕 **program slicing**\ Given a point of interest like the visualization of a plot, _flowR_ reduces the program to just the parts which are relevant for the computation of the point of interest.
Example: Slicing with flowR The simplest way to retrieve slices is with flowR's [Visual Studio Code extension](https://marketplace.visualstudio.com/items?itemName=code-inspect.vscode-flowr). However, you can slice using the [REPL](https://github.com/flowr-analysis/flowr/wiki/Interface#using-the-repl) as well. This can help you if you want to reuse specific parts of an existing analysis within another context or if you want to understand what is happening in the code. For this, let's have a look at the example file, located at [test/testfiles/example.R](https://github.com/flowr-analysis/flowr/tree/main//test/testfiles/example.R): ```r sum <- 0 product <- 1 w <- 7 N <- 10 for (i in 1:(N-1)) { sum <- sum + i + w product <- product * i } cat("Sum:", sum, "\n") cat("Product:", product, "\n") ``` Let's suppose we are interested only in the `sum` which is printed in line 11. To get a slice for this, you can use the following command: ```shell $ docker run -it --rm eagleoutice/flowr # or npm run flowr flowR repl using flowR v2.4.6, R v4.5.0 (r-shell engine) R> :slicer test/testfiles/example.R --criterion "11@sum" ```
Output ```text sum <- 0 w <- 7 N <- 10 for(i in 1:(N-1)) sum <- sum + i + w sum ```
* 📚 **dependency analysis**\ Given your analysis project, flowR offers a plethora of so-called [queries](https://github.com/flowr-analysis/flowr/wiki/Query-API) to get more information about your code. An important query is the [dependencies query](https://github.com/flowr-analysis/flowr/wiki/Query-API#dependencies-query), which shows you the library your project needs, the data files it reads, the scripts it sources, and the data it outputs.
Example: Dependency Analysis with flowR The following showcases the dependency view of the [Visual Studio Code extension](https://marketplace.visualstudio.com/items?itemName=code-inspect.vscode-flowr): ![Dependency Analysis](https://raw.githubusercontent.com/flowr-analysis/vscode-flowr/refs/heads/main/media/dependencies.png)
* 🚀 **fast data- and control-flow graphs**\ Within just 135.6 ms (as of Aug 20, 2025), _flowR_ can analyze the data- and control-flow of the average real-world R script. See the [benchmarks](https://flowr-analysis.github.io/flowr/wiki/stats/benchmark) for more information, and consult the [wiki pages](https://github.com/flowr-analysis/flowr/wiki/Dataflow-Graph) for more details on the dataflow graph.
Example: Generating a dataflow graph with flowR You can investigate flowR's analyses using the [REPL](https://github.com/flowr-analysis/flowr/wiki/Interface#using-the-repl). Commands like `:dataflow*` allow you to view a dataflow graph for a given R script. Let's have a look at the following example: ```r sum <- 0 product <- 1 w <- 7 N <- 10 for (i in 1:(N-1)) { sum <- sum + i + w product <- product * i } cat("Sum:", sum, "\n") cat("Product:", product, "\n") ``` To get the dataflow graph for this script, you can use the following command: ```shell $ docker run -it --rm eagleoutice/flowr # or npm run flowr flowR repl using flowR v2.4.6, R v4.5.0 (r-shell engine) R> :dataflow* test/testfiles/example.R ```
Output ```text https://mermaid.live/view#base64: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 ``` Following the link output should show the following: ```mermaid flowchart LR 1{{"`#91;RNumber#93; 0 (1) *1.8*`"}} 0["`#91;RSymbol#93; sum (0) *1.1-3*`"] 2[["`#91;RBinaryOp#93; #60;#45; (2) *1.1-8* (0, 1)`"]] built-in:_-["`Built-In: #60;#45;`"] style built-in:_- stroke:gray,fill:lightgray,stroke-width:2px,opacity:.8; 4{{"`#91;RNumber#93; 1 (4) *2.12*`"}} 3["`#91;RSymbol#93; product (3) *2.1-7*`"] 5[["`#91;RBinaryOp#93; #60;#45; (5) *2.1-12* (3, 4)`"]] 7{{"`#91;RNumber#93; 7 (7) *3.6*`"}} 6["`#91;RSymbol#93; w (6) *3.1*`"] 8[["`#91;RBinaryOp#93; #60;#45; (8) *3.1-6* (6, 7)`"]] 10{{"`#91;RNumber#93; 10 (10) *4.6-7*`"}} 9["`#91;RSymbol#93; N (9) *4.1*`"] 11[["`#91;RBinaryOp#93; #60;#45; (11) *4.1-7* (9, 10)`"]] 12["`#91;RSymbol#93; i (12) *6.6*`"] 13{{"`#91;RNumber#93; 1 (13) *6.11*`"}} 16(["`#91;RSymbol#93; N (16) *6.14*`"]) 17{{"`#91;RNumber#93; 1 (17) *6.16*`"}} 18[["`#91;RBinaryOp#93; #45; (18) *6.14-16* (16, 17)`"]] built-in:-["`Built-In: #45;`"] style built-in:- stroke:gray,fill:lightgray,stroke-width:2px,opacity:.8; 19[["`#91;RExpressionList#93; ( (19) *6.13* (18)`"]] built-in:_["`Built-In: (`"] style built-in:_ stroke:gray,fill:lightgray,stroke-width:2px,opacity:.8; 20[["`#91;RBinaryOp#93; #58; (20) *6.11-17* (13, 19)`"]] built-in::["`Built-In: #58;`"] style built-in:: stroke:gray,fill:lightgray,stroke-width:2px,opacity:.8; 24(["`#91;RSymbol#93; sum (24, :may:36+) *7.10-12*`"]) 25(["`#91;RSymbol#93; i (25, :may:36+) *7.16*`"]) 26[["`#91;RBinaryOp#93; #43; (26, :may:36+) *7.10-16* (24, 25)`"]] 27(["`#91;RSymbol#93; w (27, :may:36+) *7.20*`"]) 28[["`#91;RBinaryOp#93; #43; (28, :may:36+) *7.10-20* (26, 27)`"]] 23["`#91;RSymbol#93; sum (23, :may:) *7.3-5*`"] 29[["`#91;RBinaryOp#93; #60;#45; (29, :may:36+) *7.3-20* (23, 28)`"]] 31(["`#91;RSymbol#93; product (31, :may:36+) *8.14-20*`"]) 32(["`#91;RSymbol#93; i (32, :may:36+) *8.24*`"]) 33[["`#91;RBinaryOp#93; #42; (33, :may:36+) *8.14-24* (31, 32)`"]] 30["`#91;RSymbol#93; product (30, :may:) *8.3-9*`"] 34[["`#91;RBinaryOp#93; #60;#45; (34, :may:36+) *8.3-24* (30, 33)`"]] 35[["`#91;RExpressionList#93; #123; (35, :may:36+) *6.20* (29, 34)`"]] 36[["`#91;RForLoop#93; for (36) *6.1-9.1* (12, 20, 35)`"]] built-in:for["`Built-In: for`"] style built-in:for stroke:gray,fill:lightgray,stroke-width:2px,opacity:.8; 38{{"`#91;RString#93; #34;Sum#58;#34; (38) *11.5-10*`"}} 40(["`#91;RSymbol#93; sum (40) *11.13-15*`"]) built-in:sum["`Built-In: sum`"] style built-in:sum stroke:gray,fill:lightgray,stroke-width:2px,opacity:.8; 42{{"`#91;RString#93; #34; #34; (42) *11.18-21*`"}} 44[["`#91;RFunctionCall#93; cat (44) *11.1-22* (38, 40, 42)`"]] built-in:cat["`Built-In: cat`"] style built-in:cat stroke:gray,fill:lightgray,stroke-width:2px,opacity:.8; 46{{"`#91;RString#93; #34;Product#58;#34; (46) *12.5-14*`"}} 48(["`#91;RSymbol#93; product (48) *12.17-23*`"]) 50{{"`#91;RString#93; #34; #34; (50) *12.26-29*`"}} 52[["`#91;RFunctionCall#93; cat (52) *12.1-30* (46, 48, 50)`"]] 0 -->|"defined-by"| 1 0 -->|"defined-by"| 2 2 -->|"argument"| 1 2 -->|"returns, argument"| 0 2 -.->|"reads, calls"| built-in:_- linkStyle 4 stroke:gray; 3 -->|"defined-by"| 4 3 -->|"defined-by"| 5 5 -->|"argument"| 4 5 -->|"returns, argument"| 3 5 -.->|"reads, calls"| built-in:_- linkStyle 9 stroke:gray; 6 -->|"defined-by"| 7 6 -->|"defined-by"| 8 8 -->|"argument"| 7 8 -->|"returns, argument"| 6 8 -.->|"reads, calls"| built-in:_- linkStyle 14 stroke:gray; 9 -->|"defined-by"| 10 9 -->|"defined-by"| 11 11 -->|"argument"| 10 11 -->|"returns, argument"| 9 11 -.->|"reads, calls"| built-in:_- linkStyle 19 stroke:gray; 12 -->|"defined-by"| 20 16 -->|"reads"| 9 18 -->|"reads, argument"| 16 18 -->|"reads, argument"| 17 18 -.->|"reads, calls"| built-in:- linkStyle 24 stroke:gray; 19 -->|"returns, argument"| 18 19 -.->|"reads"| built-in:_ linkStyle 26 stroke:gray; 20 -->|"reads, argument"| 13 20 -->|"reads, argument"| 19 20 -.->|"reads, calls"| built-in:: linkStyle 29 stroke:gray; 24 -->|"reads"| 0 24 -->|"reads"| 23 24 -->|"CD-True"| 36 linkStyle 32 stroke:gray,color:gray; 25 -->|"reads"| 12 25 -->|"CD-True"| 36 linkStyle 34 stroke:gray,color:gray; 26 -->|"reads, argument"| 24 26 -->|"reads, argument"| 25 26 -.->|"reads, calls"| built-in:_ linkStyle 37 stroke:gray; 26 -->|"CD-True"| 36 linkStyle 38 stroke:gray,color:gray; 27 -->|"reads"| 6 27 -->|"CD-True"| 36 linkStyle 40 stroke:gray,color:gray; 28 -->|"reads, argument"| 26 28 -->|"reads, argument"| 27 28 -.->|"reads, calls"| built-in:_ linkStyle 43 stroke:gray; 28 -->|"CD-True"| 36 linkStyle 44 stroke:gray,color:gray; 23 -->|"defined-by"| 28 23 -->|"defined-by"| 29 29 -->|"argument"| 28 29 -->|"returns, argument"| 23 29 -.->|"reads, calls"| built-in:_- linkStyle 49 stroke:gray; 29 -->|"CD-True"| 36 linkStyle 50 stroke:gray,color:gray; 31 -->|"reads"| 3 31 -->|"reads"| 30 31 -->|"CD-True"| 36 linkStyle 53 stroke:gray,color:gray; 32 -->|"reads"| 12 32 -->|"CD-True"| 36 linkStyle 55 stroke:gray,color:gray; 33 -->|"reads, argument"| 31 33 -->|"reads, argument"| 32 33 -.->|"reads, calls"| built-in:_ linkStyle 58 stroke:gray; 33 -->|"CD-True"| 36 linkStyle 59 stroke:gray,color:gray; 30 -->|"defined-by"| 33 30 -->|"defined-by"| 34 34 -->|"argument"| 33 34 -->|"returns, argument"| 30 34 -.->|"reads, calls"| built-in:_- linkStyle 64 stroke:gray; 34 -->|"CD-True"| 36 linkStyle 65 stroke:gray,color:gray; 35 -->|"argument"| 29 35 -->|"returns, argument"| 34 35 -.->|"reads, calls"| built-in:_ linkStyle 68 stroke:gray; 35 -->|"CD-True"| 36 linkStyle 69 stroke:gray,color:gray; 36 -->|"argument"| 12 36 -->|"reads, argument"| 20 36 -->|"argument, non-standard-evaluation"| 35 36 -.->|"reads, calls"| built-in:for linkStyle 73 stroke:gray; 40 -->|"reads"| 0 40 -->|"reads"| 23 40 -.->|"reads"| built-in:sum linkStyle 76 stroke:gray; 44 -->|"argument"| 38 44 -->|"reads, argument"| 40 44 -->|"argument"| 42 44 -.->|"reads, calls"| built-in:cat linkStyle 80 stroke:gray; 48 -->|"reads"| 3 48 -->|"reads"| 30 52 -->|"argument"| 46 52 -->|"reads, argument"| 48 52 -->|"argument"| 50 52 -.->|"reads, calls"| built-in:cat linkStyle 86 stroke:gray; ``` (The analysis required _14.2 ms_ (including parse and normalize, using the [r-shell](https://github.com/flowr-analysis/flowr/wiki/Engines) engine) within the generation environment.)
If you want to use flowR and the features it provides, feel free to check out the: - [Visual Studio Code](https://marketplace.visualstudio.com/items?itemName=code-inspect.vscode-flowr)/[Positron](https://open-vsx.org/extension/code-inspect/vscode-flowr): provides access to flowR directly in VS Code and Positron (or [vscode.dev](https://vscode.dev/)) - [RStudio Addin](https://github.com/flowr-analysis/rstudio-addin-flowr): integrates flowR into [RStudio](https://posit.co/downloads/) - [R package](https://github.com/flowr-analysis/flowr-r-adapter): use flowR in your R scripts - [Docker image](https://hub.docker.com/r/eagleoutice/flowr): run flowR in a container, this also includes [flowR's server](https://github.com/flowr-analysis/flowr/wiki/Interface#communicating-with-the-server) - [NPM package](https://www.npmjs.com/package/@eagleoutice/flowr): include flowR in your TypeScript and JavaScript projects If you are already using flowR and want to give feedback, please consider filling out our [feedback form](https://docs.google.com/forms/d/e/1FAIpQLScKFhgnh9LGVU7QzqLvFwZe1oiv_5jNhkIO-G-zND0ppqsMxQ/viewform). ## ⭐ Getting Started To get started with _flowR_ and its features, please check out the [Overview](https://github.com/flowr-analysis/flowr/wiki/Overview) wiki page. The [Setup](https://github.com/flowr-analysis/flowr/wiki/Setup) wiki page explains how you can download and setup _flowR_ on your system. With docker 🐳️, the following line should be enough (and drop you directly into the read-eval-print loop): ```shell docker run -it --rm eagleoutice/flowr ``` You can enter `:help` to gain more information on its capabilities.
Example REPL session ![Example of a simple REPL session](wiki/gif/repl-demo-opt.gif)
## 📜 More Information For more details on how to use _flowR_ please refer to the [wiki pages](https://github.com/flowr-analysis/flowr/wiki), as well as the deployed [code documentation](https://flowr-analysis.github.io/flowr/doc/). ## 🚀 Contributing We welcome every contribution! Please check out the [developer onboarding](https://github.com/flowr-analysis/flowr/wiki/Onboarding) section in the wiki for all the information you will need. ### Contributors flowR Contributors ---- *flowr* is actively developed by [Florian Sihler](https://eagleoutice.github.io/portfolio/) under the [GPLv3 License](LICENSE).\ It is partially supported by the German Research Foundation (DFG) under the grant [504226141](https://gepris.dfg.de/gepris/projekt/504226141) ("CodeInspector"). ---- ### Generation Notice Please notice that this file was generated automatically using the file [src/documentation/print-readme.ts](https://github.com/flowr-analysis/flowr/tree/main//src/documentation/print-readme.ts) as a source.\ If you want to make changes please edit the source file (the CI will take care of the rest). In fact, many files in the [wiki](https://github.com/flowr-analysis/flowr/wiki) are generated, so make sure to check for the source file if you want to make changes.