Log files and anomalies, once again…

https://arxiv.org/pdf/2308.09324.pdf

I’ve written about log files a while back, but I think I’m getting hooked up onto the topic. It is actually quite interesting how to use it in practice. So, here is one more paper from the ASE 2023 conference.

This paper presents a new way to create log data that can help spot problems in software systems. Here’s a more casual rundown of what the paper is about:

  1. The Problem: Keeping software reliable is tough, especially when you don’t have enough good examples of system logs to train your anomaly detection tools. The logs you can get your hands on either have privacy issues or are too simple and don’t reflect real-world complexity.
  2. The Solution – AutoLog: The researchers have cooked up AutoLog, a clever method that doesn’t need to run the actual system to generate logs. It’s like a simulation game that creates realistic log data by analyzing the code of an application.
  3. How AutoLog Rolls: It works in three steps. First, it digs through the code to find all the spots where logs might happen. Then, it figures out which parts of the code could lead to those logs. Finally, it walks through these paths, creating log data that looks like it came from a real running system.
  4. The Cool Bits: AutoLog can make a lot more log events than other methods, and it does it super fast. It’s like having a log event factory that can churn out thousands of messages a minute.
  5. Flexibility for the Win: You can tweak AutoLog to simulate different scenarios, like changing the amount of data, the mix of normal and weird events, or focusing on specific parts of the system.
  6. Real-World Ready: When tested on 50 Java projects, AutoLog’s logs helped anomaly detection tools perform a bit better. It’s like giving a detective better clues to solve a case.
  7. Sharing is Caring: The team has shared AutoLog for others to use, hoping it’ll help make software more reliable by giving developers better tools for testing and benchmarking.

In short, AutoLog is a new tool for creating fake but realistic logs that can help find bugs in software without the need to mess with privacy or oversimplified data. It’s a game-changer for making sure software runs smoothly.

I need to take this tool for a spin during the upcoming break.

Author: Miroslaw Staron

I’m professor in Software Engineering at IT faculty. I usually blog about interesting articles (for me) and my own reflections on the development of Software Engineering, AI, computer science and automotive software.