I’m Misrobody, a software engineer with a mixed background in software engineering, UI/UX, and several years of study in visual arts. I like building tools, visualizers, and interfaces that make complex systems easier to understand.
For as long as I can remember, I've been dabbling in all kind of arts. However, since 2020 I've also started to mess around with the Ren'py game engine, and I've been loving it ever since!
Keep in mind that the majority of my work is available here: Itch.io
A structured overview of the technologies I use, grouped by domain for clarity.
| Category | Technologies |
|---|---|
| Languages |       |
| Formats / Markup |    |
| Front End |    |
| Databases |    |
| Tools |       |
| Methods |   |
| Frameworks & Libraries |        |
A selection of projects paired with the technologies actually used to build them. Each entry highlights a concrete deliverable that justifies the corresponding tech skills.
A narrative game built with Ren’Py and Python scripting (UI logic, event flow, asset handling).
A custom front‑end site with dynamic content loading, DOM manipulation, and handcrafted UI.
A lightweight PHP + SQLite application with server‑side logic and a minimal database layer.
A low‑level pixel‑processing tool written in C/C++ (color quantization, palette extraction).
Placeholder for an upcoming Java‑based project.
A Dockerized environment for running and distributing a usability study for the Kieker OTKT DSL.
I contributed to expanding Python support within the Kieker monitoring framework, enabling Python systems to benefit from the same depth of runtime analysis traditionally available for Java. This work involved extending instrumentation capabilities, restoring hybrid analysis tooling, and designing new visualization methods for large monitoring datasets.
The results are documented in the research paper “Grouped Graph Visualization for Kieker Monitoring Data”, available on arXiv:
arXiv:2507.23425
- Extended Kieker’s monitoring DSL to generate reliable Python instrumentation.
- Recovered and modernized the hybrid static + dynamic analysis pipeline for Python projects.
- Implemented a grouped‑graph visualization backend using Tulip, including a custom nesting algorithm.
- Built a full replication and benchmarking package across multiple Python codebases.
Delivered a functional, research‑grade monitoring pipeline for Python, complete with structured visualizations that make complex runtime behavior easier to interpret—now part of the broader Kieker ecosystem.