Yea I dont rly like git
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2 changed files with 21 additions and 10 deletions
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setup_data <- function() {
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system("get.data.bat")
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diffs <- read.delim("data/diffs.txt")
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commits <- read.csv("C:/Dev/Watchtower/data/commits.txt")
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}
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@ -4,7 +4,25 @@ author: "Jannis von Hagen"
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date: "`r Sys.Date()`"
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date: "`r Sys.Date()`"
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output: html_document
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output: html_document
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---
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---
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```{r echo=FALSE}
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```{r echo=FALSE, include=FALSE, warning = FALSE}
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source("Analyze.R")
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system("get.data.bat")
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setup_data()
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diffs <- read.delim("data/diffs.txt")
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commits <- read.csv("C:/Dev/Watchtower/data/commits.txt")
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install.packages('plyr', repos = "http://cran.us.r-project.org")
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library('plyr')
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```
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### Die Idee:
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Quellcode in Programme einzuschleußen kann es Angreifern ermöglichen
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Schadsoftware oder Sicherheitslücken auf einer großen Zahl an Geräten zu verteilen.
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Es währe also vorteilhaft wenn man Git Repositories automatisch auf auffällige Commits
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untersuchen könnte.
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Das Ziel ist es also Commits zu untersuchen, und abweichende Commits aufzuzeigen.
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```{r}
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commits_u <- count(commits$name, 'commits$name')
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barplot(commits_u$freq, names.arg=commits_u$commits.name)
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```
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```
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