diff --git a/00 Vorbemerkungen/03 git pull.ipynb b/00 Vorbemerkungen/03 git pull.ipynb
new file mode 100644
index 0000000..c149826
--- /dev/null
+++ b/00 Vorbemerkungen/03 git pull.ipynb	
@@ -0,0 +1,70 @@
+{
+ "cells": [
+  {
+   "attachments": {
+    "08a58b62-12b0-4475-b174-547941cfe692.png": {
+     "image/png": "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"
+    },
+    "52a6b4b2-9d31-4609-9ce1-85ff0cbd20c3.png": {
+     "image/png": "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"
+    },
+    "ad466bf4-2ad0-49f1-b88a-84ae4d56e9e1.png": {
+     "image/png": "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"
+    },
+    "b682de4b-a6aa-4cb0-9043-a75c51b78032.png": {
+     "image/png": "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"
+    },
+    "fe55565f-90c7-4cce-97cc-a48a76b12c7e.png": {
+     "image/png": "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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "c06472d0-6057-4425-bace-d1de48422f3f",
+   "metadata": {
+    "editable": false,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Aktuelle Daten aus dem GIT holen:\n",
+    "\n",
+    "## 1. in den Ordner `inf-abi2027` wechseln:\n",
+    "![grafik.png](attachment:fe55565f-90c7-4cce-97cc-a48a76b12c7e.png)\n",
+    "\n",
+    "## 2. links auf das GIT-Modul wechseln:\n",
+    "![grafik.png](attachment:08a58b62-12b0-4475-b174-547941cfe692.png)\n",
+    "\n",
+    "## 3. Alle Änderungen übernehmen:\n",
+    "![grafik.png](attachment:b682de4b-a6aa-4cb0-9043-a75c51b78032.png)\n",
+    "(bei **Changed** hinten auf **+**)\n",
+    "\n",
+    "## 4. Summary eingeben und auf **COMMIT** klicken:\n",
+    "![grafik.png](attachment:52a6b4b2-9d31-4609-9ce1-85ff0cbd20c3.png)\n",
+    "(egal was)\n",
+    "\n",
+    "## 5. neueste Daten abholen:\n",
+    "![grafik.png](attachment:ad466bf4-2ad0-49f1-b88a-84ae4d56e9e1.png)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Deno",
+   "language": "typescript",
+   "name": "deno"
+  },
+  "language_info": {
+   "codemirror_mode": "typescript",
+   "file_extension": ".ts",
+   "mimetype": "text/x.typescript",
+   "name": "typescript",
+   "nbconvert_exporter": "script",
+   "pygments_lexer": "typescript",
+   "version": "5.8.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/01 Einführung/05 Übungen/01 Übungen.ipynb b/01 Einführung/05 Übungen/01 Übungen.ipynb
new file mode 100644
index 0000000..d245b58
--- /dev/null
+++ b/01 Einführung/05 Übungen/01 Übungen.ipynb	
@@ -0,0 +1,700 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c9079895-47dc-4d88-b630-57c1923a0eb5",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import { assertEquals } from \"jsr:@std/assert\"\n",
+    "import \"https://git.amgdhg.de/kg/tslib/raw/branch/main/logger.ts?5\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d4b638e5-98c7-4c03-a496-cb4e0316808b",
+   "metadata": {
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Aufgabe 01.05.1 - Summe\n",
+    "\n",
+    "Programmiere eine Funktion `summe`, die zwei Zahlen als Parameter annimmt, deren Summe berechnet und anschließend zurückgibt.\n",
+    "\n",
+    "#### Hinweis:\n",
+    "\n",
+    "zurückgeben heißt: `return`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b05082a3-b2fc-46d1-9f91-d418f1861b69",
+   "metadata": {
+    "editable": false,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6b14aef1-7dc0-406a-8a7a-6d4ec4727792",
+   "metadata": {
+    "editable": false,
+    "jupyter": {
+     "source_hidden": true
+    },
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "Deno.test(\"01.05.1: function\", () => {\n",
+    "    assertEquals(typeof summe, 'function')\n",
+    "})\n",
+    "Deno.test(\"01.05.1: Parameter\", () => {\n",
+    "    assertEquals(summe.length, 2)\n",
+    "})\n",
+    "Deno.test(\"01.05.1: summe() mit verschiedenen Zufallszahlen\", () => {\n",
+    "    console.log(\"\")\n",
+    "    for (let i = 0; i < 10; i++) {\n",
+    "        let a = Math.random()\n",
+    "        let b = Math.random()\n",
+    "        console.log(\"    Teste summe(\"+a+\",\"+b+\")\")\n",
+    "        assertEquals(summe(a,b), a+b)\n",
+    "    }\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "272cc82a-2c1b-456d-86e4-5d2b7ebefc68",
+   "metadata": {
+    "editable": false,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Aufgabe 01.05.2 - Primzahlen\n",
+    "\n",
+    "Programmiere eine Funktion `istPrim`, die eine Zahl als Parameter bekommt. Die Methode soll überprüfen, ob der Parameter eine Primzahl ist und dementsprechend `true` oder `false` zurückgeben.\n",
+    "\n",
+    "#### 1. Hinweis:\n",
+    "1 ist per Definition *keine* Primzahl!\n",
+    "\n",
+    "#### 2. Hinweis:\n",
+    "da TypeScript nur allgemeine Zahltypen versteht, müssen wir hier auch überprüfen, ob es eine ganze Zahl ist! (Tipp: überprüfe, ob der übergebene Parameter durch 1 teilbar ist.)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "50ebf235-210d-439f-8906-4d56f3e70b0a",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "58073f15-9ba6-4d50-a26e-c83a5002b739",
+   "metadata": {
+    "editable": false,
+    "jupyter": {
+     "source_hidden": true
+    },
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "let _nr = \"01.05.3\"\n",
+    "Deno.test(`${_nr}: function`, () => {\n",
+    "    assertEquals(typeof istPrim, 'function')\n",
+    "})\n",
+    "Deno.test(`${_nr}: Parameter`, () => {\n",
+    "    assertEquals(istPrim.length, 1)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istPrim(2.052)=false`, () => {\n",
+    "    assertEquals(istPrim(2.052), false)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istPrim(1)=false`, () => {\n",
+    "    assertEquals(istPrim(1), false)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istPrim(2)=true`, () => {\n",
+    "    assertEquals(istPrim(2), true)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istPrim(3)=true`, () => {\n",
+    "    assertEquals(istPrim(3), true)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istPrim(4)=false`, () => {\n",
+    "    assertEquals(istPrim(4), false)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istPrim(5)=true`, () => {\n",
+    "    assertEquals(istPrim(5), true)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istPrim(72)=false`, () => {\n",
+    "    assertEquals(istPrim(72), false)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istPrim(97)=true`, () => {\n",
+    "    assertEquals(istPrim(97), true)\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1bf8c3e7-2fef-46e2-a92a-8d345b4bee5f",
+   "metadata": {
+    "editable": false,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Aufgabe 01.05.3 - Primzahl-Doubletten\n",
+    "\n",
+    "Eine Primzahl-Doublette besteht aus zwei Primzahlen, deren Differenz gleich 2 ist (z.B. <u>3 und 5</u> oder <u>11 und 13</u> oder <u>1019 und 1021</u>)\n",
+    "\n",
+    "Programmiere eine Funktion `primDoublette`, die eine Zahl `min` als Parameter annimmt. Von diesem Wert `min` soll aufsteigend nach der nächsten Primzahl-Doublette gesucht werden.\n",
+    "\n",
+    "Zurückgegeben werden soll die kleinere der beiden Zahlen (also in den obigen Beispielen 3 bzw. 11 bzw. 1019)\n",
+    "\n",
+    "#### Beispiel:\n",
+    "\n",
+    "Wird die Funktion mit dem Paramter `20` aufgerufen, soll als Ergebnis `29` zurückgegeben werden, da <u>29 und 31</u> die kleinsten Primzahl-Doubletten sind, die größer sind als `20`\n",
+    "\n",
+    "#### Hinweis:\n",
+    "\n",
+    "es soll dabei die Methode `istPrim` aus Aufgabe 01.05.2 weiterverwendet werden!*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9501c38b-8336-4c06-a09c-917e4d13bce2",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6ff22110-d320-4bf6-9241-2d87b2891e30",
+   "metadata": {
+    "editable": false,
+    "jupyter": {
+     "source_hidden": true
+    },
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "let _nr = \"01.05.3\"\n",
+    "Deno.test(`${_nr}: function`, () => {\n",
+    "    assertEquals(typeof primDoublette, 'function')\n",
+    "})\n",
+    "Deno.test(`${_nr}: Parameter`, () => {\n",
+    "    assertEquals(primDoublette.length, 1)\n",
+    "})\n",
+    "Deno.test(`${_nr}: primDoublette(1)=3`, () => {\n",
+    "    assertEquals(primDoublette(1), 3)\n",
+    "})\n",
+    "Deno.test(`${_nr}: primDoublette(10)=11`, () => {\n",
+    "    assertEquals(primDoublette(10), 11)\n",
+    "})\n",
+    "Deno.test(`${_nr}: primDoublette(50)=59`, () => {\n",
+    "    assertEquals(primDoublette(50), 59)\n",
+    "})\n",
+    "Deno.test(`${_nr}: primDoublette(100)=101`, () => {\n",
+    "    assertEquals(primDoublette(100), 101)\n",
+    "})\n",
+    "Deno.test(`${_nr}: primDoublette(1000)=1019`, () => {\n",
+    "    assertEquals(primDoublette(1000), 1019)\n",
+    "})\n",
+    "Deno.test(`${_nr}: primDoublette(59108)=59207`, () => {\n",
+    "    assertEquals(primDoublette(59108), 59207)\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f10e6386-bec1-43b9-8a45-15dc6bd9a4a4",
+   "metadata": {
+    "editable": false,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Aufgabe 01.05.4 - Pythagoräische Tripel\n",
+    "\n",
+    "Ein pythagoräisches Tripel besteht aus drei ganzen Zahlen `a`, `b` und `c`, die zusammen die Bedingung $a^2+b^2=c^2$ erfüllen, wie z.B. (3,4,5)\n",
+    "\n",
+    "Programmiere eine Funktion `pytTripel` ohne Parameter, die sämtliche Pythagoräischen Tripel auf der Konsole ausgibt für $a,b,c \\leq 100$\n",
+    "\n",
+    "Außerdem soll gelten: $a\\leq b$. Die Ausgabe soll leerzeichengetrennt erfolgen, also\n",
+    "```\n",
+    "3 4 5\n",
+    "5 12 13\n",
+    "6 8 10\n",
+    "[...]\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eb8318be-02b9-44d5-aa1e-15455ea74b9f",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8473f71c-3e33-4321-8ed4-d5fdd85b946b",
+   "metadata": {
+    "editable": false,
+    "jupyter": {
+     "source_hidden": true
+    },
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "let _nr = \"01.05.4\"\n",
+    "Deno.test(`${_nr}: function`, () => {\n",
+    "    assertEquals(typeof pytTripel, 'function')\n",
+    "})\n",
+    "Deno.test(`${_nr}: Parameter`, () => {\n",
+    "    assertEquals(pytTripel.length, 0)\n",
+    "})\n",
+    "Deno.test(`${_nr}: pytTripel()`, () => {\n",
+    "    console.start(false)\n",
+    "    pytTripel()\n",
+    "    let result = console.end().split(\"\\n\")\n",
+    "    \n",
+    "    assertEquals(result.length, 52, \"nicht korrekte Anzahl ausgegeben\")\n",
+    "    for(let i = 0; i < result.length; i++) {\n",
+    "        const row = result[i].split(\" \").map(x => parseInt(x))\n",
+    "        assertEquals(row[0]*row[0] + row[1]*row[1], row[2]*row[2], \"ungültiges Tripel ausgegeben\")\n",
+    "\n",
+    "        if (i < result.length - 1) {\n",
+    "            const next = result[i + 1].split(\" \").map(x => parseInt(x))\n",
+    "            assertEquals(row[0] === next[0] && row[1] === next[1], false, \"zwei gleiche Tripel ausgegeben\")\n",
+    "        }\n",
+    "    }\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1489f365-a169-46d0-9349-b482db1d5d75",
+   "metadata": {
+    "editable": false,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Aufgabe 01.05.5 - lineare Nullstelle\n",
+    "\n",
+    "Schreibe eine Funktion `linNst`, die die Nullstelle einer linearen Funktion $f(x) = m\\cdot x + c$ berechnet.\n",
+    "\n",
+    "Als Parameter sollen `m` und `c` eingegeben werden, zurückgegeben werden soll der `x`-Wert der Nullstelle.\n",
+    "\n",
+    "#### mathematischer Hinweis:\n",
+    "Eine lineare Funktion hat immer eine Nullstelle, außer mit $a=0$ und $b\\neq0$. Bei $a=0$ und $b=0$ gibt es unendlich viele Nullstellen. Diese Sonderfälle müssen hier nicht beachtet werden!\n",
+    "\n",
+    "#### Tipp:\n",
+    "Für eine Nullstelle gilt $y=0$. Anschließend kann nach $x$ umgeformt werden."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1faf34b0-553d-49ae-87c2-92c335b97aab",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a6012f7-8be8-4b6b-aa28-06d9dc9d4bdb",
+   "metadata": {
+    "editable": false,
+    "jupyter": {
+     "source_hidden": true
+    },
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "let _nr = \"01.05.5\"\n",
+    "Deno.test(`${_nr}: function`, () => {\n",
+    "    assertEquals(typeof linNst, 'function')\n",
+    "})\n",
+    "Deno.test(`${_nr}: Parameter`, () => {\n",
+    "    assertEquals(linNst.length, 2)\n",
+    "})\n",
+    "Deno.test(`${_nr}: linNst(1,0)=0`, () => {\n",
+    "    assertEquals(linNst(1,0), 0)\n",
+    "})\n",
+    "Deno.test(`${_nr}: linNst(5,0)=0`, () => {\n",
+    "    assertEquals(linNst(5,0), 0)\n",
+    "})\n",
+    "Deno.test(`${_nr}: linNst(2,4)=-2`, () => {\n",
+    "    assertEquals(linNst(2,4), -2)\n",
+    "})\n",
+    "Deno.test(`${_nr}: linNst(4,2)=-0.5`, () => {\n",
+    "    assertEquals(linNst(4,2), -0.5)\n",
+    "})\n",
+    "Deno.test(`${_nr}: linNst(-0.6,9)=15`, () => {\n",
+    "    assertEquals(linNst(-0.6,9), 15)\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e420032b-ed4d-4e4e-80f8-0b14d5f0cc2b",
+   "metadata": {
+    "editable": false,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Aufgabe 01.05.6 - quadratische Nullstellen\n",
+    "\n",
+    "Äquivalent zur Aufgabe 01.05.5 soll nun die Funktion `quadNst` programmiert werden, die die Nullstellen einer quadratischen Funktion $f(x)=a\\cdot x^2+b\\cdot x + c$ berechnet.\n",
+    "\n",
+    "Als Parameter sollen die Werte für $a$, $b$ und $c$ eingegeben werden.\n",
+    "\n",
+    "Zurückgegeben werden sollen *alle* möglichen Nullstellen.\n",
+    "\n",
+    "#### Hinweis:\n",
+    "\n",
+    "Um mehrere Werte zurückgeben zu können, kann folgende Schreibweise genutzt werden:\n",
+    "* `return []` gibt ein leeres Ergebnis zurück (= keine Nullstelle)\n",
+    "* `return [x1]` gibt ein Ergebnis mit einer Nullstelle $x_1$ zurück\n",
+    "* `return [x1, x2]` gibt ein Ergebnis mit zwei Nullstellen $x_1$ und $x_2$ zurück.\n",
+    "\n",
+    "#### 2. Hinweis:\n",
+    "\n",
+    "Die Wurzel eines Wertes $D$ lässt sich mit `Math.sqrt(D)` berechnen.\n",
+    "\n",
+    "#### mathematischer Hinweis:\n",
+    "\n",
+    "Die Nullstellen einer quadratischen Funktion berechnet man mit der Mitternachtsformel. Die Diskriminante (= Radikand = Wert unter der Wurzel) entscheidet darüber, wie viele Nullstellen es gibt."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a49e6ce5-ba34-406c-ab1a-99745a09e468",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09b15d57-2e91-45d4-ae06-e4872bbfc777",
+   "metadata": {
+    "editable": false,
+    "jupyter": {
+     "source_hidden": true
+    },
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "let _nr = \"01.05.6\"\n",
+    "Deno.test(`${_nr}: function`, () => {\n",
+    "    assertEquals(typeof quadNst, 'function')\n",
+    "})\n",
+    "Deno.test(`${_nr}: Parameter`, () => {\n",
+    "    assertEquals(quadNst.length, 3)\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(1,-5,6)=[2,3]`, () => {\n",
+    "    const res = quadNst(1,-5,6)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 2)\n",
+    "    assertEquals(res.sort(), [2,3])\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(1,-3,2)=[1,2]`, () => {\n",
+    "    const res = quadNst(1,-3,2)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 2)\n",
+    "    assertEquals(res.sort(), [1,2])\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(2,-8,6)=[1,3]`, () => {\n",
+    "    const res = quadNst(2,-8,6)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 2)\n",
+    "    assertEquals(res.sort(), [1,3])\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(3,-12,9)=[1,3]`, () => {\n",
+    "    const res = quadNst(3,-12,9)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 2)\n",
+    "    assertEquals(res.sort(), [1,3])\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(-1,7,-12)=[3,4]`, () => {\n",
+    "    const res = quadNst(-1,7,-12)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 2)\n",
+    "    assertEquals(res.sort(), [3,4])\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(1,-4,4)=[2]`, () => {\n",
+    "    const res = quadNst(1,-4,4)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 1)\n",
+    "    assertEquals(res.sort(), [2])\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(-2,8,-8)=[2]`, () => {\n",
+    "    const res = quadNst(-2,8,-8)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 1)\n",
+    "    assertEquals(res.sort(), [2])\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(3,6,3)=[-1]`, () => {\n",
+    "    const res = quadNst(3,6,3)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 1)\n",
+    "    assertEquals(res.sort(), [-1])\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(1,2,5)=[]`, () => {\n",
+    "    const res = quadNst(1,2,5)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 0)\n",
+    "})\n",
+    "Deno.test(`${_nr}: quadNst(2,4,6)=[]`, () => {\n",
+    "    const res = quadNst(2,4,6)\n",
+    "    assertEquals(Array.isArray(res), true)\n",
+    "    assertEquals(res.length, 0)\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a213d25b-b301-4cd9-9ada-9ad914bfff0f",
+   "metadata": {
+    "editable": false,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "# Aufgabe 01.05.7 - Sonntage zählen\n",
+    "Die folgenden Informationen sind gegeben:\n",
+    "* der 1. Januar 1900 war ein Montag\n",
+    "* 30 Tage haben folgende Monate: April, Juni, September und November\n",
+    "* der Februar hat 28 Tage, in Schaltjahren 29 Tage\n",
+    "* alle anderen Monate haben 31 Tage\n",
+    "\n",
+    "## Teilaufgabe 1:\n",
+    "Programmiere eine Funktion `istSchaltjahr`, die als Parameter eine Jahreszahl bekommt und `true` oder `false` zurückgibt.\n",
+    "\n",
+    "## Teilaufgabe 2:\n",
+    "Programmiere eine Funktion `tageImMonat`, die als Parameter Monat und Jahr übergeben bekommt und die Anzahl der Tage in diesem Monat zurückgibt\n",
+    "\n",
+    "## Teilaufgabe 3:\n",
+    "* Programmiere eine Methode `ausgabe`, die mithilfe von Schleifen zunächst alle Datumsangaben vom 1.1.1900 bis zum 31.12.2000 ausgibt, z.B.\n",
+    "```\n",
+    "1.1.1900\n",
+    "2.1.1900\n",
+    "3.1.1900\n",
+    "[...]\n",
+    "30.12.1900\n",
+    "31.12.1900\n",
+    "```\n",
+    "\n",
+    "Ergänze die Ausgabe anschließend um den Wochentag, z.B.\n",
+    "```\n",
+    "1.1.1900 Montag\n",
+    "2.1.1900 Dienstag\n",
+    "[...]\n",
+    "```\n",
+    "\n",
+    "#### Hinweis:\n",
+    "Das Ergebnis dieser Methode wird nicht überprüft!\n",
+    "\n",
+    "## Teilaufgabe 4:\n",
+    "Programmiere eine Funktion `sonntage`, die als Parameter eine Jahreszahl übergeben bekommt und die Sonntage vom 1.1.1900 bis zum 31.12. des als Parameter angegebenen Jahres **zählt** und die Anzahl zurückgibt.\n",
+    "\n",
+    "#### Beispiel:\n",
+    "* `sonntage(1900)` zählt die Sonntage zwischen dem 1.1.1900 und 31.12.1900 und gibt als Ergebnis `52` zurück\n",
+    "* `sonntage(2000)` gibt als Ergebnis `5270` zurück"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "19f1f81e-fb48-4fee-a2a3-e047a254e521",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bb3c5d55-fe18-4445-8cb7-734a9e19768b",
+   "metadata": {
+    "editable": false,
+    "jupyter": {
+     "source_hidden": true
+    },
+    "scrolled": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "let _nr = \"01.05.6.1\"\n",
+    "Deno.test(`${_nr}: function`, () => {\n",
+    "    assertEquals(typeof istSchaltjahr, 'function')\n",
+    "})\n",
+    "Deno.test(`${_nr}: Parameter`, () => {\n",
+    "    assertEquals(istSchaltjahr.length, 1)\n",
+    "})\n",
+    "Deno.test(`${_nr}: istSchaltjahr`, () => {\n",
+    "    assertEquals(istSchaltjahr(0), true)\n",
+    "    assertEquals(istSchaltjahr(2024), true)\n",
+    "    assertEquals(istSchaltjahr(2025), false)\n",
+    "    assertEquals(istSchaltjahr(1900), false)\n",
+    "    assertEquals(istSchaltjahr(2000), true)\n",
+    "})\n",
+    "_nr = \"01.05.6.2\"\n",
+    "Deno.test(`${_nr}: function`, () => {\n",
+    "    assertEquals(typeof tageImMonat, 'function')\n",
+    "})\n",
+    "Deno.test(`${_nr}: Parameter`, () => {\n",
+    "    assertEquals(tageImMonat.length, 2)\n",
+    "})\n",
+    "Deno.test(`${_nr}: tageImMonat`, () => {\n",
+    "    assertEquals(tageImMonat(1,1900), 31)\n",
+    "    assertEquals(tageImMonat(2,1900), 28)\n",
+    "    assertEquals(tageImMonat(2,2000), 29)\n",
+    "    assertEquals(tageImMonat(3,1964), 31)\n",
+    "    assertEquals(tageImMonat(4,1786), 30)\n",
+    "})\n",
+    "_nr = \"01.05.6.4\"\n",
+    "Deno.test(`${_nr}: function`, () => {\n",
+    "    assertEquals(typeof sonntage, 'function')\n",
+    "})\n",
+    "Deno.test(`${_nr}: Parameter`, () => {\n",
+    "    assertEquals(sonntage.length, 1)\n",
+    "})\n",
+    "Deno.test(`${_nr}: sonntage`, () => {\n",
+    "    assertEquals(sonntage(1900), 52)\n",
+    "    \n",
+    "    const a = (new Date(\"1900-01-01\")).getTime()\n",
+    "    for (let i = 0; i < 100; i++) {\n",
+    "        const y = Math.round(1900 + Math.random()*125)\n",
+    "        const b = (new Date(`${y+1}-01-01`)).getTime()\n",
+    "        const c = b-a\n",
+    "        const s = Math.floor(c/3600000/24/7)\n",
+    "\n",
+    "        assertEquals(sonntage(y), s)\n",
+    "    }\n",
+    "})"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Deno",
+   "language": "typescript",
+   "name": "deno"
+  },
+  "language_info": {
+   "codemirror_mode": "typescript",
+   "file_extension": ".ts",
+   "mimetype": "text/x.typescript",
+   "name": "typescript",
+   "nbconvert_exporter": "script",
+   "pygments_lexer": "typescript",
+   "version": "5.8.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}