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\begin{document}
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\maketitle
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\begin{adjustwidth}{-4cm}{-4cm}
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\centering
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\begin{tabular}{cc}
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\toprule
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Repository URL & \url{https://github.com/kamclassroom2022/project-02-python-test-generator-maggicl} \\
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Commit ID & \texttt{--} \\ \bottomrule
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\end{tabular}
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\end{adjustwidth}
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\vspace{1cm}
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\subsection*{Section 1 - Instrumentation}
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effect-size has been used to measure the significance of the difference. Results of the statistical analysis are
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shown in table~\ref{tab:stats}.
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Only 3 benchmark files out of 10 make the two script have statistical different performance. They are namely
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\textit{check\_armstrong}, \textit{rabin\_karp} and \textit{anagram\_check}. The first two show that the genetic algorithm
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performs significantly better than the fuzzer, while the last file shows the opposite.
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Only 4 benchmark files out of 10 make the two script have statistical different performance. They are namely
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\textit{check\_armstrong}, \textit{zeller\_birthday}, \textit{rabin\_karp} and \textit{anagram\_check}.
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The first three show that the genetic algorithm performs significantly better than the fuzzer,
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while the last file shows the opposite.
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\end{document}
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