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36 Zeilen
2.6 KiB
TeX
36 Zeilen
2.6 KiB
TeX
vor 3 Wochen
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\texttt{GNU ddrescue}\footnote{GNU ddrescue: \url{https://www.gnu.org/software/ddrescue/}, hereinafter referred to as \texttt{ddrescue}, not to be confused with the older \texttt{dd\_rescue}} is a data recovery utility
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that allows the transfer of data from one file or block device (such as hard disks, CD-ROMs, etc.) to another.
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Unlike the eponymous tool \texttt{dd}, it focuses on the retrieval of undamaged parts in the event of read errors.
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The basic operation of ddrescue is fully automated, eliminating the need for manual error handling or program restart.
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The \textbf{mapfile}, a unique feature of \texttt{ddrescue}, is a core feature for its efficiency.
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The mapfile allows data to be retrieved efficiently by reading only the necessary blocks.
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It also allows to interrupt the rescue process at any point and resume later at the same point.
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\texttt{ddrescueview}\footnote{ddrescueview: \url{https://sourceforge.net/projects/ddrescueview/}} is a graphical interface for \texttt{ddrescue} mapfiles.
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It visualizes \texttt{ddrescue}'s mapfiles via a user-friendly GUI\@.
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The main view shows a grid, with the colour of each cell indicating the rescue status of the blocks it represents.
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Both tools are used for data recovery, both in private and professional environments, for example in IT forensics\cite[p. 130]{tatort2017}.
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However, these tools are not always executed on a system with a graphical user interface.
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In forensic applications, for example, it is common to work mainly under Windows,
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as professional software is sometimes only supported there.
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However, as \texttt{ddrescue} requires a unix-like operating system,
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a small separate Linux is often used for this purpose,
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which in some cases does not offer a graphical user interface.
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\texttt{ddrescue} itself is a command line application, so there is mainly a need for another application
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that visualises mapfiles on the terminal and thus provides more precise information on the progress of a backup.
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The implementation of this other application is described in the following sections,
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starting with the parsing of the mapfiles.
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\subsection{Writing process}\label{subsec:writing-process}
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In the writing process of this report, artificial neural networks were used for selected and individual purposes.
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The online translation service DeepL, which according to the company is based on machine-learning methods
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such as Transformers and Convolutional Neural Networks, was used as a formulation aid.
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LLMs, specifically ChatGPT with GPT-4, were inter alia used to simplify the manual creation of latex code
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such as tables and bibliography entries and for generating the abstract,
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however everything was still corrected and adjusted by hand.
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