์ธ๋„ค์ผ CursorAI + MCP ๋กœ ์ƒ์‚ฐ์„ฑ 100๋ฐฐ ๋ถ€์ŠคํŠธํ•˜๊ธฐ (Sequential Thinking๊ณผ TalkToFigma) CursorAI์™€ MCP(Model Context Protocol)๋Š” ๊ฐœ๋ฐœ์ž์—๊ฒŒ ๊ฐ•๋ ฅํ•œ ๋„๊ตฌ๋กœ ์„ธ์ƒ์ด ์‹œ๋„๋Ÿฝ๋‹ค. CursorAI ์— ํฌ๊ฒŒ ๋†€๋ž๋Š”๋ฐ, MCP ๋ฅผ ๊ฒฐํ•ฉํ•˜๋ฉด ๋” ์—„์ฒญ๋‚˜๋‹ค๋Š” ์ด์•ผ๊ธฐ๋ฅผ ์œ ํŠœ๋ธŒ์—์„œ ๋ณด๊ณ  ๋ช‡๊ฐ€์ง€ ํ™œ์šฉํ•ด๋ณด์•˜๋‹ค. CursorAI์™€ MCP์˜ ์†Œ๊ฐœCursorAI๋Š” ์ธ๊ณต์ง€๋Šฅ์„ ํ™œ์šฉํ•˜์—ฌ ์ฝ”๋“œ ์ž‘์„ฑ, ๋””๋ฒ„๊น…, ์ตœ์ ํ™” ๋“ฑ์„ ์ง€์›ํ•˜๋Š” ๋„๊ตฌ๋กœ, ๊ฐœ๋ฐœ์ž์˜ ์ƒ์‚ฐ์„ฑ์„ ํฌ๊ฒŒ ํ–ฅ์ƒ์‹œํ‚จ๋‹ค. MCP๋Š” ๋‹ค์–‘ํ•œ ํ”Œ๋žซํผ๊ณผ์˜ ํ†ตํ•ฉ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜์—ฌ, ๊ฐœ๋ฐœ์ž๊ฐ€ ์—ฌ๋Ÿฌ ๋„๊ตฌ๋ฅผ ์œ ๊ธฐ์ ์œผ๋กœ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•๋Š”๋‹ค.๋‚ด๊ฐ€ ์‚ฌ์šฉํ•ด๋ณธ MCP 1 -  Sequential Thinking ๐Ÿง Sequential Thinking์€ ๋ณต์žกํ•œ ๋ฌธ์ œ๋ฅผ ๋‹จ๊ณ„๋ณ„๋กœ ์ ‘๊ทผํ•˜์—ฌ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ์œผ๋กœ, ๊ฐœ๋ฐœ ๊ณผ์ •์—์„œ์˜ ๋…ผ๋ฆฌ์  ์‚ฌ๊ณ ๋ฅผ ๊ฐ•ํ™”ํ•œ๋‹ค. ๋‹จ๊ณ„๋ณ„๋กœ ๋ช…ํ™•ํ•˜๊ฒŒ ..
์ธ๋„ค์ผ Cursor AI ๋“ฑ .. ์ฝ”๋”ฉํ•  ๋•Œ AI ํˆด์„ ์‚ฌ์šฉํ•˜๋ฉฐ ๋Š๋‚€ ๊ฐœ์ธ์ ์ธ ์ƒ๊ฐ, ๋ถ€์ž‘์šฉ AI ์ฝ”๋”ฉ์˜ ์œ„ํ—˜์„ฑ์˜ค๋Š˜ ์‹ค์ œ ํ”„๋กœ์ ํŠธ ๋งˆ์ด๊ทธ๋ ˆ์ด์…˜์„ ์ง„ํ–‰ํ•˜๋ฉด์„œ ๊นจ๋‹ฌ์€ ์ค‘์š”ํ•œ ์ ์ด ์žˆ์Šต๋‹ˆ๋‹ค.์ฝ”๋“œ์— ๋Œ€ํ•œ ๊นŠ์€ ์ดํ•ด ์—†์ด AI๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ์€ ๋งค์šฐ ์œ„ํ—˜ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์‚ฌ์‹ค์ž…๋‹ˆ๋‹ค.๊ธฐ์กด ์ฝ”๋“œ๋Š” ์ œ๊ฐ€ ์ง์ ‘ ๊ธฐ๋Šฅ์„ ๊ตฌ์ƒํ•˜๊ณ , ํ•˜๋‚˜์”ฉ ํ•จ์ˆ˜๋ฅผ ์ž‘์„ฑํ•œ, ๊ทธ์•ผ๋ง๋กœ '์ดํ•ด๋„๊ฐ€ ๋†’์€ ์ฝ”๋“œ' ์˜€์Šต๋‹ˆ๋‹ค. ์˜ค๋Š˜ cursorAI ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํƒ€์ž…์Šคํฌ๋ฆฝํŠธ๋กœ ๋งˆ์ด๊ทธ๋ ˆ์ด์…˜ํ•˜๊ณ , ๊ธฐ์กด์˜ Redux ์ ์šฉ ๋ฒ”์œ„๋ฅผ ํ™•์žฅํ•˜๋ฉด์„œ ์ฃผ์˜ํ•˜๊ณ , ๋‹ค์Œ๋ถ€ํ„ด ์–ด๋–ป๊ฒŒ ํ•ด์•ผํ•  ์ง€ ํšŒ๊ณ ๊ฐ€ ํ•„์š”ํ•  ๊ฒƒ ๊ฐ™์•„์„œ ์ด ๊ธ€์„ ์ž‘์„ฑํ•˜๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.  1. ์™œ ์œ„ํ—˜ํ•œ๊ฐ€?์ฒซ๋ฒˆ์งธ๋กœ ๊ธฐ๋Šฅ ์†์ƒ์˜ ์œ„ํ—˜์ด ํฝ๋‹ˆ๋‹ค. AI๊ฐ€ ์ฝ”๋“œ์˜ ์ „์ฒด์ ์ธ ๋งฅ๋ฝ์„ ์™„๋ฒฝํžˆ ์ดํ•ดํ•˜์ง€ ๋ชปํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ์ƒ๊ฐ๋ณด๋‹ค ๋งŽ์•˜์Šต๋‹ˆ๋‹ค. ๊ทธ๋ž˜์„œ ๊ธฐ์กด ๊ธฐ๋Šฅ์˜ ์˜๋„๋‚˜ ๋กœ์ง์„ ๋ณด์กดํ•˜์ง€ ๋ชปํ•œ ๊ฒƒ์„ ๋’ค๋Šฆ๊ฒŒ ๋ฐœ๊ฒฌํ•˜๊ธฐ๋„ ํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‘๋ฒˆ์งธ๋กœ..
๋ฆฌ์•กํŠธ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ -> ํƒ€์ž…์Šคํฌ๋ฆฝํŠธ๋กœ ๋งˆ์ด๊ทธ๋ ˆ์ด์…˜ ํ•˜๊ธฐ! 1. ์ปดํฌ๋„ŒํŠธ ์„ ์–ธ ๋ฐฉ์‹// ๊ธฐ์กด JSconst Dashboard = () => { // ...}// ๋ณ€ํ™˜๋œ TSXconst Dashboard: React.FC = () => { // ...}React.FC (Function Component) ํƒ€์ž…์„ ๋ช…์‹œ์ ์œผ๋กœ ์„ ์–ธํ•˜์—ฌ TypeScript์—๊ฒŒ ์ด ์ปดํฌ๋„ŒํŠธ๊ฐ€ React ์ปดํฌ๋„ŒํŠธ์ž„์„ ์•Œ๋ ค์ค€๋‹ค์ด๋ ‡๊ฒŒ ํ•˜๋ฉด ์ปดํฌ๋„ŒํŠธ์˜ props ํƒ€์ž…์„ ์ž๋™์œผ๋กœ ์ถ”๋ก ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, React ๊ด€๋ จ ํƒ€์ž… ์ฒดํฌ๋„ ๊ฐ€๋Šฅํ•˜๋‹ค์ตœ์‹  React์—์„œ๋Š” React.FC ๋Œ€์‹  React.ComponentType์„ ์‚ฌ์šฉํ•˜๋Š” ๊ฒฝ์šฐ๋„ ์žˆ๋‹ค 2. Props ํƒ€์ž… ์ •์˜// ๊ธฐ์กด JSconst CategoryEditor = ({ onClose }) => { // ...}// ๋ณ€ํ™˜๋œ TSXinterfac..
์ธ๋„ค์ผ ๐ŸŒ— Styled Components๋กœ ๋ผ์ดํŠธ/๋‹คํฌ ๋ชจ๋“œ ์ „ํ™˜ํ•˜๊ธฐ ์‹ค์ œ ํ”„๋กœ์ ํŠธ์—์„œ๋Š” ์‚ฌ์šฉ์ž์—๊ฒŒ ๋‹คํฌ ๋ชจ๋“œ์™€ ๋ผ์ดํŠธ ๋ชจ๋“œ๋ฅผ ์ œ๊ณตํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•œ UX ์š”์†Œ ์ค‘ ํ•˜๋‚˜์ด๋‹ค.styled-components์™€ ThemeProvider๋ฅผ ํ™œ์šฉํ•˜๋ฉด ์ „์—ญ ํ…Œ๋งˆ ์ „ํ™˜์„ ๋งค์šฐ ๊ฐ„๋‹จํ•˜๊ฒŒ ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ๋‹ค.โœ… 1. ํ…Œ๋งˆ ๊ฐ์ฒด ์ •์˜ํ•˜๊ธฐ// themes.jsexport const lightTheme = { textColor: "#111", backgroundColor: "whitesmoke",};export const darkTheme = { textColor: "whitesmoke", backgroundColor: "#111",};โœ… 2. App์—์„œ ํ…Œ๋งˆ ์ƒํƒœ ๊ด€๋ฆฌ์—ฌ๋Ÿฌ๊ฐœ์˜ property๋ฅผ ๊ฐ€์ง„ ๊ฐ์ฒด๋ฅผ ๋‘๊ฐœ (๋‹คํฌ/๋ผ์ดํŠธ) ์„ค์ •ํ•จ์œผ๋กœ์จ ๊ฐ„ํŽธํ•˜๊ฒŒ theme์„ ๋ฐ”๊ฟ€ ์ˆ˜ ์žˆ๋‹ค.  // Ap..
์ธ๋„ค์ผ Styled Components - ์• ๋‹ˆ๋ฉ”์ด์…˜, ์ปดํฌ๋„ŒํŠธ ์„ ํƒ์ž, ์ค‘์ฒฉ ์Šคํƒ€์ผ๋ง ์ด๋ฒˆ์— ๋”๋“ฌ์–ด๋ณผ ๊ธฐ์–ต์€ ..  keyframes ๋„ const ๋กœ ๋”ฐ๋กœ ๋นผ์„œ ๊ด€๋ฆฌํ•˜๋Š” ๊ฑฐ + styled component ์กฐ๊ฑด๋ฌธ์ฒ˜๋Ÿผ ์“ฐ๊ธฐ !! โœ… ํšŒ์ „ ์• ๋‹ˆ๋ฉ”์ด์…˜ ๋งŒ๋“ค๊ธฐ๋จผ์ € keyframes๋ฅผ ์‚ฌ์šฉํ•ด ํšŒ์ „ํ•˜๋Š” ์• ๋‹ˆ๋ฉ”์ด์…˜์„ ์ •์˜ํ•œ๋‹ค.import styled, { keyframes } from "styled-components"; const rotationAnimation = keyframes` 0% { transform: rotate(0deg); border-radius: 0px; } 50% { border-radius: 100px; } 100% { transform: rotate(360deg); border-radiu..
์ธ๋„ค์ผ Styled Component์—์„œ ์ปดํฌ๋„ŒํŠธ ํ™•์žฅํ•˜๊ธฐ ์˜›๋‚ ์— ๋ฆฌ์•กํŠธ ์ฒ˜์Œ ์ตํž๋•Œ ๋‹ค ๊ณต๋ถ€ํ–ˆ๋˜ ๊ฒƒ ๊ฐ™์€๋ฐ, ํ”„๋กœ์ ํŠธ๋“ค์„ ํ•˜๋‹ค๋ณด๋‹ˆ ๋น„์Šทํ•œ ์ปดํฌ๋„ŒํŠธ๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋งŽ์€๋ฐ ๋ฌด์‹œํ•˜๊ณ  ๊ณ„์† ํ•˜๋‹ค๊ฐ€ .. '์•„ ์˜›๋‚ ์— ์ด๊ฑฐ ๊ณต๋ถ€ํ–ˆ์—ˆ๋Š”๋ฐ .. ' ์‹ถ์–ด์„œ ์ •๋ฆฌํ•˜๊ฒŒ๋๋‹ค.  ์ผ๋‹จ ๊ทธ ์ „์— styled component ๋ฅผ ์“ฐ๋Š” ์ด์œ ๋Š” ๊ธฐ์กด์— div๋ฅผ ๋งŒ๋“ค๊ณ  className ์ด๋‚˜ style์„ ๋ถ€์—ฌํ•˜๋Š” ์‹์ด์—ˆ์ง€๋งŒ,๋Œ€์‹  styled๋ฅผ ์ž„ํฌํŠธ ํ•ด์„œ ์šฐ๋ฆฌ๊ฐ€ ์‚ฌ์šฉํ•  html ์—์„œ ์‚ฌ์šฉํ•˜๊ณ  ์‹ถ์€ ํƒœ๊ทธ๋ฅผ ์ง€์ •ํ•˜๊ณ , ๋ฐฑํ‹ฑ ์•ˆ์— css์ฝ”๋“œ๋ฅผ ์ ์–ด์ค€๋‹ค. -> ์ปดํฌ๋„ŒํŠธ ์ด๋ ‡๊ฒŒ ํ•˜๊ฒŒ ๋˜๋ฉด ์Šคํƒ€์ผ๋ง ๋œ ์ปดํฌ๋„ŒํŠธ๋ฅผ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ, ์ปดํฌ๋„ŒํŠธ ํ•จ์ˆ˜ ์•ˆ์— ์Šคํƒ€์ผ์„ ์ ์„ ํ•„์š”๊ฐ€ ์—†๊ณ , ๊ฐ€๋…์„ฑ์ด ์ข‹์•„์ง„๋‹ค.  ๋‚˜๋Š” ํผ์งํ•œ or ๋งŽ์ด ์‚ฌ์šฉํ• ๋งŒํ•œ ์ปดํฌ๋„ŒํŠธ๋“ค์€ ์Šคํƒ€์ผ ์ปดํฌ๋„ŒํŠธ๋กœ ์ง€์ •ํ•˜๊ณ , ๊ทธ ์•ˆ์˜ ์ž์ž˜ํ•œ ํ…์ŠคํŠธ๋‚˜ ๋ฒ„..
์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ์—์„œ์˜ BFS์™€ DFS 1. BFS (Breadth-First Search)BFS๋Š” ์‹œ์ž‘ ๋…ธ๋“œ์—์„œ๋ถ€ํ„ฐ ๊ฐ€๊นŒ์šด ๋…ธ๋“œ๋ถ€ํ„ฐ ์ฐจ๋ก€๋กœ ๋ฐฉ๋ฌธํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ž…๋‹ˆ๋‹ค.๋ณดํ†ต ํ(Queue, FIFO: First-In, First-Out)๋ฅผ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค.์ตœ๋‹จ ๊ฒฝ๋กœ, ๋ ˆ๋ฒจ ์ˆœํšŒ ๋“ฑ์— ์œ ์šฉํ•ฉ๋‹ˆ๋‹ค.function bfsWithVisited(start, getNeighbors) { const queue = [start]; const visited = new Set(); visited.add(start); console.log("์ดˆ๊ธฐ visited:", Array.from(visited)); while (queue.length > 0) { const current = queue.shift(); // ํ์—์„œ ๊ฐ€์žฅ ์•ž์˜ ์›..
์ธ๋„ค์ผ 17. ๋™์  ํ”„๋กœ๊ทธ๋ž˜๋ฐ (Dynamic Programming) Codility Lesson ํ•œ๊ตญ์–ด ์ •๋ฆฌ๋ณธ (JavaScript ver.) ๋™์  ํ”„๋กœ๊ทธ๋ž˜๋ฐ(Dynamic Programming)์ด๋ž€?๋™์  ํ”„๋กœ๊ทธ๋ž˜๋ฐ(DP)์€ ์ž‘์€ ๋ฌธ์ œ๋“ค์˜ ํ•ด๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋” ํฐ ๋ฌธ์ œ์˜ ํ•ด๋ฅผ ๊ตฌํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ธฐ๋ฒ• ์ด๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ๋ฌธ์ œ๋ฅผ ์—ฌ๋Ÿฌ ์ž‘์€ ๋ถ€๋ถ„ ๋ฌธ์ œ๋กœ ๋‚˜๋ˆ„๊ณ , ์ค‘๋ณต ๊ณ„์‚ฐ์„ ์ค„์ด๊ธฐ ์œ„ํ•ด ๊ฒฐ๊ณผ๋ฅผ ์ €์žฅ(memoization) ํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ์‚ฌ์šฉ๋œ๋‹ค.๋™์  ํ”„๋กœ๊ทธ๋ž˜๋ฐ์ด ํšจ๊ณผ์ ์ธ ๊ฒฝ์šฐ:์ตœ์  ๋ถ€๋ถ„ ๊ตฌ์กฐ(Optimal Substructure): ํฐ ๋ฌธ์ œ์˜ ์ตœ์ ํ•ด๊ฐ€ ์ž‘์€ ๋ถ€๋ถ„ ๋ฌธ์ œ์˜ ์ตœ์ ํ•ด๋กœ ๊ตฌ์„ฑ๋  ์ˆ˜ ์žˆ์Œ์ค‘๋ณต ๋ถ€๋ถ„ ๋ฌธ์ œ(Overlapping Subproblems): ๋™์ผํ•œ ์ž‘์€ ๋ฌธ์ œ๋ฅผ ์—ฌ๋Ÿฌ ๋ฒˆ ํ•ด๊ฒฐํ•ด์•ผ ํ•˜๋Š” ๊ฒฝ์šฐ๋Œ€ํ‘œ์ ์ธ DP ๋ฌธ์ œ:์ตœ๋‹จ ๊ฒฝ๋กœ ๋ฌธ์ œ (Floyd-Warshall, Bellman-Ford)๋ฐฐ๋‚ญ ๋ฌธ์ œ (Knapsack Problem)๋™์ „ ๊ฑฐ์Šค๋ฆ„๋ˆ ๋ฌธ์ œ (Coi..
์ธ๋„ค์ผ 16. ํƒ์š•์  ์•Œ๊ณ ๋ฆฌ์ฆ˜ (Greedy Algorithms) Codility Lesson ํ•œ๊ตญ์–ด ์ •๋ฆฌ๋ณธ (JavaScript ver.) ํƒ์š•์  ์•Œ๊ณ ๋ฆฌ์ฆ˜(Greedy Algorithm)์ด๋ž€?ํƒ์š•์  ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๊ฐ ๋‹จ๊ณ„์—์„œ ๊ฐ€์žฅ ์ตœ์„ ์˜ ์„ ํƒ์„ ํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ์ตœ์ ํ•ด๋ฅผ ์ฐพ๋Š” ๋ฐฉ๋ฒ• ์ด๋‹ค. ์ „์ฒด ์ตœ์ ํ•ด๋ฅผ ๊ณ ๋ คํ•˜์ง€ ์•Š๊ณ , ๋งค ์ˆœ๊ฐ„ ์ตœ์ ์˜ ์„ ํƒ์„ ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๊ตฌํ˜„์ด ๊ฐ„๋‹จํ•˜์ง€๋งŒ, ํ•ญ์ƒ ์ตœ์ ํ•ด๋ฅผ ๋ณด์žฅํ•˜๋Š” ๊ฒƒ์€ ์•„๋‹ˆ๋‹ค.ํƒ์š•์  ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ ์šฉ๋  ์ˆ˜ ์žˆ๋Š” ๋Œ€ํ‘œ์ ์ธ ๋ฌธ์ œ๋“ค:๋™์ „ ๊ฑฐ์Šค๋ฆ„๋ˆ ๋ฌธ์ œ (Coin Change Problem)ํšŒ์˜์‹ค ๋ฐฐ์ • ๋ฌธ์ œ (Activity Selection Problem)๋ฐฐ๋‚ญ ๋ฌธ์ œ (Knapsack Problem)์ž‘์—… ์Šค์ผ€์ค„๋ง ๋ฌธ์ œ (Activity Selection)์ตœ์†Œ ์‹ ์žฅ ํŠธ๋ฆฌ (MST, Minimum Spanning Tree)ํ—ˆํ”„๋งŒ ์ฝ”๋”ฉ (Huffman Coding)ํƒ์š• ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํŠน์ง•๋น ๋ฅธ ์‹คํ–‰ ์‹œ๊ฐ„: O(n log n) ๋˜๋Š” O(..