Skip to main content

Do your bugs lurk?

Adam Barr has a great post about debugging: Software Engineering Goal: Expose Bugs Faster in which he suggests that the critical task in improving software engineering is decreasing, not the bug count, but the lurkability of bugs.

FoxPro is terrible for lurking bugs. Think of C5 errors. If you have a missing object pointer somewhere, it will generate a C5 error. but not immediately - just later on at some point in time.

Yes, we know about some resolutions to this (Don't Return Inside With), but it's a great example of a lurker.

Which is one of the reasons why tools such as Coverage Profiler and FoxUnit exist - (read Eric Sink's great post about Code Coverage). It's also one of the reasons behind my earlier work on the Code Analyst, as part of VFPX.

I'm getting ready to get started on building further betas on this (Randy Jean had asked me about it at the beginning of last month and I have been too buried to get into it). We've already got a list of some of the more basic checks to find lurking bugs (such as looking for RETURNS inside ENDWITH) as well as more cosmetic ones.

If you haven't seen the earlier versions of it, you can see a little of it in action here.

What tips do you use to catch your lurking bugs?

Comments

Popular posts from this blog

Elevating Project Specifications with Three Insightful ChatGPT Prompts

For developers and testers, ChatGPT, the freely accessible tool from OpenAI, is game-changing. If you want to learn a new programming language, ask for samples or have it convert your existing code. This can be done in Visual Studio Code (using GitHub CoPilot) or directly in the ChatGPT app or web site.  If you’re a tester, ChatGPT can write a test spec or actual test code (if you use Jest or Cypress) based on existing code, copied and pasted into the input area. But ChatGPT can be of huge value for analysts (whether system or business) who need to validate their needs. There’s often a disconnect between developers and analysts. Analysts complain that developers don’t build what they asked for or ask too many questions. Developers complain that analysts haven’t thought of obvious things. In these situations, ChatGPT can be a great intermediary. At its worst, it forces you to think about and then discount obvious issues. At best, it clarifies the needs into documented requirements. ...

Friend vs Therapist vs LLM: Shades of Grey

The conversations with AI series brings up a single point and then compares it between different LLM engines. These types of conversations were one of the many contributing factors to my writing of " Towards Consciousness " that explores the benefits and issues of creating a conscious AI. In this scenario, I was interested in seeing how an LLM might differ from a friend or therapist on issues that may have nuanced responses or contexts. In doing so, I came up with an interesting discussion on shades of grey. My Premise: Is it a bit strange to be using an LLM as a sober second thought? Every time I walk down this path of “why use an LLM to do certain things”, I come back to the alternatives that people like to say. “Why not bring it up with a friend?” A friend typically has your back or will say whatever to support their own agenda. “A therapist?” That’s someone who is “trained” to be impartial. But a computer? A computer is impartial based on two logical outcomes. If you say ...

Respect

Respect is something humans give to each other through personal connection. It’s the bond that forms when we recognize something—or someone—as significant, relatable, or worthy of care. This connection doesn’t have to be limited to people. There was an  article  recently that described the differing attitudes towards AI tools such as ChatGPT and Google Gemini (formerly Bard). Some people treat them like a standard search while others form a sort of personal relationship — being courteous, saying “please” and “thank you”. Occasionally, people share extra details unrelated to their question, like, ‘I’m going to a wedding. What flower goes well with a tuxedo?’ Does an AI “care” how you respond to it? Of course not — it reflects the patterns it’s trained on. Yet our interaction shapes how these tools evolve, and that influence is something we should take seriously. Most of us have all expressed frustration when an AI “hallucinates”. Real or not, the larger issue is that we have hi...