The hottest Debugging Substack posts right now

And their main takeaways
Category
Top Technology Topics
Data Science Daily 0 implied HN points 05 Apr 23
  1. There are numerous workflow orchestrators available for data scientists to choose from.
  2. Consider the tool's design, local/remote running capabilities, and ease of interacting with output when selecting a workflow orchestrator.
  3. Choose a workflow orchestrator based on your specific use case, whether it's for data engineers, ML engineers, or data scientists.
Barn Lab 0 implied HN points 10 Feb 24
  1. NSA released Ghidra as an open-source reverse engineering tool, making it popular in college curriculums and cybersecurity operations.
  2. Ghidra is valued for its ability to analyze and secure software without running potentially malicious code directly on the host system.
  3. Tools like BinWalk for firmware extraction and platforms like Crackmes.One offer resources for legal software cracking and reverse engineering exploration.
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Thái | Hacker | Kỹ sư tin tặc 0 implied HN points 17 Jul 07
  1. Spammers can go to extreme lengths to disrupt anti-spam systems, such as overwhelming them with strange spam emails.
  2. Technical challenges in dealing with spam, like a spam email causing a crucial software component to crash, require thorough investigation and debugging techniques.
  3. In the ongoing battle against spam, spammers may resort to sacrificial tactics, like using spam emails to specifically target and disable anti-spam software.
Paul’s Substack 0 implied HN points 15 Jun 24
  1. Development often involves failure, iteration, and debugging until a program becomes stable enough to ship.
  2. To cope with an iterative workflow, consider writing software that generates code, allowing you to easily make changes and regenerate code as needed.
  3. Creating little DSLs specific to each project, using tools like PEG parsing, can help simplify coding, debugging, and adapting to new insights about the problem space.
realkinetic 0 implied HN points 19 Mar 24
  1. When developing AWS data pipelines with Lambda and S3, setting up unit tests early can catch bugs and speed up development time.
  2. Using tools like VSCode and Jest can help streamline the testing process for AWS infrastructure code.
  3. Utilizing mock libraries like aws-sdk-client-mock allows for effective testing of data processing functions in Lambda.