Add Day 1

Author: itsdevdom

day-1/README.md

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+# Day 1: Historian Hysteria
+
+<br>
+
+## Part 1
+
+You haven't even left yet and the group of Elvish Senior Historians has already hit a problem: their list of locations to check is currently
+**empty**. Eventually, someone decides that the best place to check first would be the Chief Historian's office.
+
+Upon pouring into the office, everyone confirms that the Chief Historian is indeed nowhere to be found. Instead, the Elves discover an
+assortment of notes and lists of historically significant locations! This seems to be the planning the Chief Historian was doing before he
+left. Perhaps these notes can be used to determine which locations to search?
+
+Throughout the Chief's office, the historically significant locations are listed not by name but by a unique number called the **location
+ID**. To make sure they don't miss anything, The Historians split into two groups, each searching the office and trying to create their own
+complete list of location IDs.
+
+There's just one problem: by holding the two lists up **side by side** (your puzzle input), it quickly becomes clear that the lists aren't
+very similar. Maybe you can help The Historians reconcile their lists?
+
+For example:
+
+```txt
+3   4
+4   3
+2   5
+1   3
+3   9
+3   3
+```
+
+Maybe the lists are only off by a small amount! To find out, pair up the numbers and measure how far apart they are. Pair up the **smallest
+number in the left list** with the **smallest number in the right list**, then the **second-smallest left number** with the
+**second-smallest right number**, and so on.
+
+Within each pair, figure out **how far apart** the two numbers are; you'll need to **add up all of those distances**. For example, if you
+pair up a `3` from the left list with a `7` from the right list, the distance apart is `4`; if you pair up a `9` with a `3`, the distance
+apart is `6`.
+
+In the example list above, the pairs and distances would be as follows:
+
+- The smallest number in the left list is `1`, and the smallest number in the right list is `3`. The distance between them is `2`.
+- The second-smallest number in the left list is `2`, and the second-smallest number in the right list is another `3`. The distance between
+  them is `1`.
+- The third-smallest number in both lists is `3`, so the distance between them is `0`.
+- The next numbers to pair up are `3` and `4`, a distance of `1`.
+- The fifth-smallest numbers in each list are `3` and `5`, a distance of `2`.
+- Finally, the largest number in the left list is `4`, while the largest number in the right list is `9`; these are a distance `5` apart.
+
+To find the **total distance** between the left list and the right list, add up the distances between all of the pairs you found. In the
+example above, this is `2 + 1 + 0 + 1 + 2 + 5`, a total distance of `11`!
+
+Your actual left and right lists contain many location IDs. **What is the total distance between your lists?**
+
+<br>
+
+## Part 2
+
+Your analysis only confirmed what everyone feared: the two lists of location IDs are indeed very different.
+
+Or are they?
+
+The Historians can't agree on which group made the mistakes **or** how to read most of the Chief's handwriting, but in the commotion you
+notice an interesting detail: a lot of location IDs appear in both lists! Maybe the other numbers aren't location IDs at all but rather
+misinterpreted handwriting.
+
+This time, you'll need to figure out exactly how often each number from the left list appears in the right list. Calculate a total
+**similarity score** by adding up each number in the left list after multiplying it by the number of times that number appears in the right
+list.
+
+Here are the same example lists again:
+
+```txt
+3   4
+4   3
+2   5
+1   3
+3   9
+3   3
+```
+
+For these example lists, here is the process of finding the similarity score:
+
+- The first number in the left list is `3`. It appears in the right list three times, so the similarity score increases by `3 * 3 = 9`.
+- The second number in the left list is `4`. It appears in the right list once, so the similarity score increases by `4 * 1 = 4`.
+- The third number in the left list is `2`. It does not appear in the right list, so the similarity score does not increase (`2 * 0 = 0`).
+- The fourth number, `1`, also does not appear in the right list.
+- The fifth number, `3`, appears in the right list three times; the similarity score increases by `9`.
+- The last number, `3`, appears in the right list three times; the similarity score again increases by `9`.
+
+So, for these example lists, the similarity score at the end of this process is `31` (`9 + 4 + 0 + 0 + 9 + 9`).
+
+Once again consider your left and right lists. **What is their similarity score?**

day-1/day-1.test.ts

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+import { describe, it } from 'node:test';
+import assert from 'node:assert';
+import path from 'node:path';
+
+import { calculateSimilarityScore, calculateTotalDistance } from './day-1';
+
+describe('Day 1: Historian Hysteria', () => {
+  const locationIdListsFilePath = path.join(__dirname, 'location-id-lists.txt');
+
+  it('Part 1: should calculate total distance', async () => {
+    const expectedTotalDistance = 1873376; // Verified for this dataset
+
+    const calculatedTotalDistance = await calculateTotalDistance(locationIdListsFilePath);
+
+    assert.strictEqual(calculatedTotalDistance, expectedTotalDistance);
+  });
+
+  it('Part 2: should calculate similarity score', async () => {
+    const expectedSimilarityScore = 18997088; // Verified for this dataset
+
+    const calculatedTotalDistance = await calculateSimilarityScore(locationIdListsFilePath);
+
+    assert.strictEqual(calculatedTotalDistance, expectedSimilarityScore);
+  });
+});

day-1/day-1.ts

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+import fs from 'node:fs/promises';
+
+/**
+ * Read file
+ */
+const readFile = async (filePath: string): Promise<string> => {
+  const fileContents = await fs.readFile(filePath, {
+    encoding: 'utf8',
+  });
+  const normalizedFileContents = fileContents.trim().split(/\r?\n/).join('\n');
+  return normalizedFileContents;
+};
+
+/**
+ * Parse location ID lists
+ */
+const parseLocationIdLists = (locationIdListsFileContent: string): [Array<number>, Array<number>] => {
+  // Get all location IDs by file line (horizontal)
+  const locationIdsPerFileLine = locationIdListsFileContent.split('\n').map((fileContentLine) => {
+    return [...fileContentLine.matchAll(/\d+/g)]
+      .map((locationIdMatch) => {
+        return locationIdMatch[0];
+      })
+      .map((locationIdAsString) => {
+        return parseInt(locationIdAsString, 10);
+      });
+  });
+
+  // Group location IDs into lists (vertical)
+  const locationIdLists: [Array<number>, Array<number>] = [[], []];
+  for (let fileLineIndex = 0; fileLineIndex < locationIdsPerFileLine.length; fileLineIndex++) {
+    for (let locationIdIndex = 0; locationIdIndex < locationIdsPerFileLine[fileLineIndex].length; locationIdIndex++) {
+      locationIdLists[locationIdIndex][fileLineIndex] = locationIdsPerFileLine[fileLineIndex][locationIdIndex];
+    }
+  }
+
+  // Done
+  return locationIdLists;
+};
+
+/**
+ * Part 1: Calculate total distance
+ */
+export const calculateTotalDistance = async (locationIdListsFilePath: string) => {
+  // Get data
+  const locationIdListsFileContent = await readFile(locationIdListsFilePath);
+  const locationIdLists = parseLocationIdLists(locationIdListsFileContent);
+
+  // Sort lists
+  locationIdLists.forEach((locationList) => {
+    locationList.sort(); // Note: Mutates existing array
+  });
+
+  // Calculate total distance
+  let totalDistance = 0;
+  for (let locationIdListIndex = 0; locationIdListIndex < locationIdLists[0].length; locationIdListIndex++) {
+    totalDistance += Math.abs(locationIdLists[0][locationIdListIndex] - locationIdLists[1][locationIdListIndex]);
+  }
+
+  // Done
+  return totalDistance;
+};
+
+/**
+ * Part 2: Calculate similarity score
+ */
+export const calculateSimilarityScore = async (locationIdListsFilePath: string) => {
+  // Get data
+  const locationIdListsFileContent = await readFile(locationIdListsFilePath);
+  const locationIdLists = parseLocationIdLists(locationIdListsFileContent);
+
+  // Get similarity score
+  let similarityScore = 0;
+  for (let locationIdListIndex = 0; locationIdListIndex < locationIdLists[0].length; locationIdListIndex++) {
+    let countIdenticalLocationIds = 0;
+    for (let secondLocationIdListIndex = 0; secondLocationIdListIndex < locationIdLists[1].length; secondLocationIdListIndex++) {
+      if (locationIdLists[1][secondLocationIdListIndex] === locationIdLists[0][locationIdListIndex]) {
+        countIdenticalLocationIds++;
+      }
+    }
+    similarityScore += countIdenticalLocationIds * locationIdLists[0][locationIdListIndex];
+  }
+
+  // Done
+  return similarityScore;
+};