Add landing page information.

UncertaintySourceArchive/src/views/HomeView.vue

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 <template>
   <main class="flex h-full flex-col items-center text-center">
     <img src="https://raw.githubusercontent.com/abunai-dev/.github/main/profile/abunai-art.png" />
+
     <h1 class="text-3xl font-bold">ARC<sup>3</sup>N</h1>
     <h3 class="text-xl">
       Rese<b>ARC</b>h <b>ARC</b>hive for Software-<b>ARC</b>hitectural U<b>N</b>certainty
     </h3>
-    <p class="my-5">Toller Beispiel Text</p>
-    <RouterLink to="/archive">
-      <ButtonComponent>Go to Archive</ButtonComponent>
-    </RouterLink>
+
+    <p class="mb-3 mt-10 w-3/6 text-left">
+      Model-based confidentiality analyses help identify confidentiality violations already at
+      design time <span class="text-xs italic">[1]</span>. However, uncertainty both within software
+      systems and their environment <span class="text-xs italic">[2]</span> voids statements about
+      confidentiality and must be considered in the analysis process
+      <span class="text-xs italic">[3]</span>. The lack of awareness about uncertainty sources is
+      even more challenging as it limits the comprehensiveness of uncertainty-aware analysis
+      <span class="text-xs italic">[4]</span>.
+    </p>
+
+    <p class="mb-3 w-3/6 text-left">
+      To address this limitation, this <span class="font-bold">research archive</span> collects
+      uncertainty sources with a potential impact on confidentiality. Based on an existing
+      classification of uncertainty <span class="text-xs italic">[5]</span>, researchers and
+      practitioners can identify relevant uncertainty sources and better understand their properties
+      or find related uncertainty sources. The collection can be easily extended by the community.
+      The identified uncertainty sources can be exported and used in uncertainty impact analysis
+      <span class="text-xs italic">[6]</span> or uncertainty-aware confidentiality analysis
+      <span class="text-xs italic">[7, 8]</span>.
+    </p>
+
+    <p class="my-0.5 mb-8 w-3/6 text-left">
+      <span class="font-bold">ARC<sup>3</sup>N</span> is part of the
+      <span class="font-bold">ABUNAI</span> research project which provides a comprehensive process
+      of uncertainty-aware confidentiality analysis <span class="text-xs italic">[3]</span>. To
+      learn more about the project, visit the project website.
+    </p>
+
+    <div class="inline-flex space-x-3">
+      <RouterLink to="/archive">
+        <ButtonComponent class="p-1 pl-3 pr-3">Go to the archive</ButtonComponent>
+      </RouterLink>
+      <RouterLink to="/category">
+        <ButtonComponent class="p-1 pl-3 pr-3">Go to the classification</ButtonComponent>
+      </RouterLink>
+      <a href="https://abunai.dev">
+        <ButtonComponent class="p-1 pl-3 pr-3">Visit the project website</ButtonComponent>
+      </a>
+    </div>
+
+    <p class="mt-20 w-3/6 text-left text-xs italic">
+      [1] S. Seifermann, et al., "Detecting violations of access control and information flow
+      policies in data flow diagrams", JSS, vol. 184, Elsevier, 2022.<br />
+      [2] M. Acosta, et al., "Uncertainty in coupled models of cyber-physical systems", MODELS-C,
+      ACM, 2022.<br />
+      [3] S. Hahner, "Architectural Access Control Policy Refinement and Verification under
+      Uncertainty", ECSA-C, 2021.<br />
+      [4] D. Garlan, "The Unknown Unknowns Are Not Totally Unknown", SEAMS, IEEE/ACM, 2021.<br />
+      [5] S. Hahner, et al., "A Classification of Software-Architectural Uncertainty Regarding
+      Confidentiality", ICETE, Springer, 2023.<br />
+      [6] S. Hahner, et al., "Architecture-Based Uncertainty Impact Analysis to Ensure
+      Confidentiality", SEAMS, IEEE/ACM, 2023.<br />
+      [7] S. Hahner, et al., "Model-based Confidentiality Analysis under Uncertainty", ICSA-C, IEEE,
+      2023.<br />
+      [8] M. Walter, et al., "Architectural Optimization for Confidentiality Under Structural
+      Uncertainty", ECSA, Springer, 2022.
+    </p>
   </main>
 </template>