This is part two of my journey creating a Java (Line) Coverage Analyzer. Here we’ll actually implement the Byte Code Instrumentation, as pointed out in the first part. Since processing the Byte Code itself, i.e. reading the classes, finding the methods, processing line number information, is in itself a huge task, let’s rely on the ASM library for that. After all JaCoCo and Cobertura also rely on that, so this seems to be a valid choice 😂...

Have you ever wondered what happens when you click on “Run with Coverage” in IntelliJ? Obviously it’s running the tests, but how is it collecting the coverage information? Let’s create a simple Line Coverage Analyzer in and for Java 🥳 First of all, let’s write a simple example program (see GitHub) package de.brokenpipe.dojo.undercovered.demo; public class Demo { public static void main(final String[] argv) { final String greeting = "Hello World"; bla(greeting); bla("to the blarg"); } private static void bla(final String greeting) { System....

Pretty likely this is a well-known thing to many 🥱, and to be honest, I also kindof knew that Chromium has some search shortcuts, but I never bothered to learn how to use them. To even add to that, I’m even well aware that I quite regularly went to pages like dict.leo.org, and used the search feature there. Or I went to our Jira instance, and used the search feature there, regularly just typing a ticket number....

This is the fourth (and likely last) part in this mini series. ℹ️ This post belongs to a mini series (I’m aiming for three posts in a row), where I try prompting Claude with different levels of verbosity and compare the results: In Claude writing a Telegram Bot, 1st try I’m using an elaborate, step-by-step prompting strategy with Haiku model In Claude writing a Telegram Bot, 2nd try I aim for a detailed one-shot prompt In Claude writing a Telegram Bot, 3rd try I try a rather short one-shot prompt In Other LLMs writing a Telegram Bot I quickly try DeepSeek and some more LLMs Since DeepSeek currently is all the rage, obviously I had to prompt it as well....

This is the third part of the mini series on writing Telegram bots to read my gas meter using Claude. ℹ️ This post belongs to a mini series (I’m aiming for three posts in a row), where I try prompting Claude with different levels of verbosity and compare the results: In Claude writing a Telegram Bot, 1st try I’m using an elaborate, step-by-step prompting strategy with Haiku model In Claude writing a Telegram Bot, 2nd try I aim for a detailed one-shot prompt In Claude writing a Telegram Bot, 3rd try I try a rather short one-shot prompt In Other LLMs writing a Telegram Bot I quickly try DeepSeek and some more LLMs Like in the first round, I will once more show the full dialog I’ve used to let it generate the implementation....

For quite some time now, I’ve been using Logseq as my personal knowledge management system. It has been an invaluable tool for organizing my thoughts, projects, and ideas. A few months ago, I decided to take it a step further by incorporating journaling into my daily routine. Each morning and evening, I reflect on how I’m feeling, what has moved me, what went well during the day, where I excelled, and where there might be room for improvement....

This is the second part of the mini series on writing Telegram bots to read my gas meter using Claude. ℹ️ This post belongs to a mini series (I’m aiming for three posts in a row), where I try prompting Claude with different levels of verbosity and compare the results: In Claude writing a Telegram Bot, 1st try I’m using an elaborate, step-by-step prompting strategy with Haiku model In Claude writing a Telegram Bot, 2nd try I aim for a detailed one-shot prompt In Claude writing a Telegram Bot, 3rd try I try a rather short one-shot prompt In Other LLMs writing a Telegram Bot I quickly try DeepSeek and some more LLMs Like in the first round, I will first show the full dialog I’ve used to let it generate the implementation....

Below you’ll find results of my initial try in using Claude to write a Telegram Bot. ℹ️ This post belongs to a mini series (I’m aiming for three posts in a row), where I try prompting Claude with different levels of verbosity and compare the results: In Claude writing a Telegram Bot, 1st try I’m using an elaborate, step-by-step prompting strategy with Haiku model In Claude writing a Telegram Bot, 2nd try I aim for a detailed one-shot prompt In Claude writing a Telegram Bot, 3rd try I try a rather short one-shot prompt In Other LLMs writing a Telegram Bot I quickly try DeepSeek and some more LLMs My ultimate goal is to figure out how much gas I need to heat my apartment....

Am 29. Juni war ich auf dem wunderbaren 6. SoCraTes Day Franken (große Empfehlung, falls es eine nächste Version geben wird). In der Session „Shift Left Testing“ von Felix Tensing beleuchtete er die Herausforderungen und seine Lösungsansätze im Bereich der Software-Anforderungsabdeckung. Hierbei stellte er sein Konzept vor, das speziell das Problem von inhaltlich veralteten oder unvollständigen Jira-Tickets adressiert. Problemstellung Jira-Tickets oder ähnliche Systeme dienen dazu, Anforderungen und Aufgaben im Entwicklungsprozess festzuhalten....

Lately, I’ve come across the concepts of “learning in public” and “digital gardens.” A digital garden is a unique approach to organizing and sharing knowledge in a non-linear and evolving manner. Think of it as a personal wiki where one can cultivate ideas, insights, and resources over time. Unlike traditional blogs or websites that present polished and finalized content, digital gardens focus on capturing the learning process itself, fostering exploration and serendipitous connections between different pieces of information....