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+---
+author: Claudio Maggioni
+title: Information Modelling & Analysis -- Project 1
+---
+
+<!--
+The following shows a minimal submission report for project 1. If you
+choose to use this template, replace all template instructions (the
+yellow bits) with your own values. In addition, for any section, if
+**and only if** anything was unclear or warnings were raised by the
+code, and you had to take assumptions about the correct implementation
+(e.g., about details of a metric), describe your assumptions in one or
+two sentences.
+
+You may - at your own risk - also choose not to use this template. As
+long as your submission is a latex-generated, English PDF containing all
+expected info, you'll be fine.
+-->
+
+# Code Repository
+
+The code and result files part of this submission can be found at:
+
+::: center
+Repository: \url{https://github.com/infoMA2023/project-01-god-classes-maggicl}
+
+Commit ID: **TBD**
+:::
+
+# Data Pre-Processing
+
+## God Classes
+
+::: {#tab:god_classes}
+  ---------------------------------------------- ---------------
+  **Class Name**                                  **\# Methods**
+  org.apache.xerces.dom.CoreDocumentImpl           125
+  org.apache.xerces.impl.xs.traversers.XSDHandler  118
+  org.apache.xerces.xinclude.XIncludeHandler       116
+  org.apache.xerces.impl.dtd.DTDGrammar            101
+  ---------------------------------------------- ---------------
+
+  : Identified God Classes
+:::
+
+The god classes I identified, and their corresponding number of methods
+can be found in Table [1](#tab:god_classes){reference-type="ref"
+reference="tab:god_classes"}.
+
+## Feature Vectors
+
+Table [2](#tab:feat_vec){reference-type="ref" reference="tab:feat_vec"}
+shows aggregate numbers regarding the extracted feature vectors for the
+god classes.
+
+::: {#tab:feat_vec}
+  ---------------- ------------------------ ---------------------
+  **Class Name**    **\# Feature Vectors**   **\# Attributes\***
+  \...                       \...                   \...
+  ---------------- ------------------------ ---------------------
+
+  : Feature vector summary (\*= used at least once)
+:::
+
+# Clustering {#sec:clustering}
+
+## Algorithm Configurations
+
+Report/comment the algorithm configurations (distance function, linkage
+rule, etc.). You may do so in any form you feel suited, but a short
+paragraph of text is probably sufficient.
+
+## Testing Various K & Silhouette Scores
+
+\(1\) Report data about the clusters produced by the two algorithms at
+various k (#clusters, size of clusters, silhouette scores). You may use
+any suitable format (table, graph, \...).
+
+\(2\) Briefly comment your results. What is the best configuration, and
+why? Anything else you observed?
+
+# Evaluation
+
+## Ground Truth
+
+I computed the ground truth using the command \.... The generated files
+are checked into the repository with the names \....
+
+Comment briefly on the strengths & weaknesses of our ground truth.
+
+## Precision and Recall
+
+::: {#tab:eval}
+  ---------------- ------------------- -------- ------------- --------
+  **Class Name**    **Agglomerative**            **K-Means**  
+                          Prec.         Recall      Prec.      Recall
+  \...                    \...           \...       \...        \...
+  ---------------- ------------------- -------- ------------- --------
+
+  : Evaluation Summary
+:::
+
+Precision and Recall, for the optimal configurations found in Section
+[3](#sec:clustering){reference-type="ref" reference="sec:clustering"},
+are reported in Table [3](#tab:eval){reference-type="ref"
+reference="tab:eval"}.
+
+## Practical Usefulness
+
+Discuss the practical usefulness of the obtained code refactoring
+assistant in a realistic setting (1 paragraph).
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