Software developer based in South Korea, working at MSI.
I build applications across backend services, web UIs, Flutter clients, and systems tooling — with deep experience in manufacturing / quality (MES · QMS) and the semiconductor domain, plus interest in practical AI for factory and quality workflows.

halukkilincer.com

I work between real product needs and maintainable code. Some of that work sits in industrial quality systems; some of it is general software — APIs, companion UIs, mobile apps, and small focused tools. I care about clear structure, readable delivery, and solutions that match the problem.

• Backend services and APIs (Spring Boot, Python)
• Web UIs and internal tools (React, Next.js, vanilla JS)
• Mobile / desktop clients (Flutter, Java Swing)
• Systems and CLI tooling (C++17, Python stdlib)
• Manufacturing & quality domain (MES · QMS · semiconductor)
• Practical AI for operations and quality workflows

A balanced sample across backend, quality UI, mobile, desktop, web tools, and systems — not only one domain.

JWT-based identity and user management REST API (Spring Boot). Registration, login, profile access, local/Docker setup.

Next.js quality board for inspection and NCR summaries over the QMS backend services.

Flutter mobile client for Soy Cicloviajera — auth, OpenStreetMap locations, and traveler profiles.

Focused multi-note desktop editor in Java Swing — persistence, import/export, simple daily-writing UI.

Client-side table helpers: search, status filter, column sort, and pagination with an accessible demo.

C++17 maze generator (DFS) and BFS solver with ASCII and optional SVG output.

Selected links by theme (not a full dump of every repo).

Quality / factory

• qms-inspection-service — inspection API (planned → completed, optional NCR link)
• qms-ncr-service — NCR REST API with workflow transitions
• ncr-console — browser console for NCR create/list/status
• lot-viewer — lot CSV metrics viewer with MAD outlier flags
• lot-metrics — Python CLI for lot aggregation / outliers

APIs & consoles

• user-api — Spring Boot User CRUD (H2 / Docker Postgres)
• user-console — Vite React UI for user-api
• api-console — browser HTTP request console
• ops-ledger — hash-routed operations ledger demo (localStorage)

Web & Flutter tools

• form-validator — accessible client-side validation rules
• fetch-queue — concurrent Fetch pool with retries / abort
• palette-studio — Flutter palette builder + WCAG-ish contrast
• receipt-split — Flutter bill split (tax, tip, shares)

Python / data CLIs

• async-fetcher — asyncio concurrent HTTP fetch CLI
• http-probe — stdlib HTTP health / latency probe
• schema-guard — JSON Schema subset validator
• log-sift — access/app log summarizer
• secret-scan — local secret-pattern scanner
• taskflow — tiny dependency-aware DAG runner
• cli-report — terminal renderer for QA JSON summaries

Systems & C++

• formula-vm — tiny expression language on a stack VM
• pixel-forge — PPM image toolkit (gray / blur / Sobel)
• json-mini — small JSON parse / pretty / validate CLI
• git-stats — Git commit / author summary CLI
• redis-lite — educational Redis-like TCP server

Learning / older

• adventure-engine — fantasy text RPG (Java)
• realm-quest — cyberpunk neon-heist text RPG (Java)
• teacher-information-system — school admin REST API

I prefer software that stays understandable after the first release: clear structure, readable code, and enough delivery detail that someone else can run and extend the project quickly.

Comfortable across Java and Python backends, React/Next.js frontends, Flutter mobile, and C++ systems tooling.

Languages     Java · Python · Dart · TypeScript · JavaScript · C · C++
Backend       Spring Boot · Django · REST APIs
Frontend      React · Next.js · Vite · Flutter
Security      Spring Security · JWT · OAuth2
Data          PostgreSQL · Redis · SQLite · H2
Tools         Maven · Docker · Git · Linux
Approach      Clean Code · SOLID · Maintainable architecture
Domains       MES · QMS · Semiconductor · Factory systems · General product software · AI in manufacturing

• Practical AI for quality and manufacturing workflows
• Identity and API security patterns
• Cleaner delivery setups (CI, Docker, docs that stay short)
• Product software that still benefits from semiconductor / factory domain knowledge

Open to conversations about industrial software, product engineering, MES/QMS platforms, and practical AI for manufacturing — as well as general backend, Flutter, and systems work.

• GitHub: github.com/Erwinya
• Website: halukkilincer.com
• X / Twitter: @ChKilincer