Google Gemini AI Offers Advice re: Hubitat Device Drivers

When asked for ways to improve my blossoming dev skillz, Google Gemini replied, "Here are some Groovy coding techniques to improve the efficiency of your Device Driver files on Hubitat™":

GENERAL TECHNIQUES

  • @CompileStatic annotation: Apply this annotation to sections of critical code to enable static type checking and improve performance by allowing the JVM to optimize better.

  • Primitive types: Prefer primitive types like int and long over their boxed counterparts like Integer and Long whenever possible, since primitives are more efficient in terms of memory and processing.

  • Collections: Choose the right collection data structure for the job. Arrays are faster for random access, while ArrayLists are better for frequent insertions and deletions. Consider immutable collections like Guava's ImmutableList for thread safety and reduced memory overhead.

  • Avoid closures: Closures create overhead because they are dynamically dispatched at runtime. If possible, replace them with explicit loops or methods.

  • as keyword: This is convenient but incurs type checking overhead. Use explicit casting ((int) value) for better performance when type information is known.

  • Profiling: Use profilers like YourKit or JProfiler to identify performance bottlenecks and focus optimization efforts on those areas.

HUBITAT-SPECIFIC TECHNIQUES:

  • Hubitat SDK methods: Use the provided Hubitat SDK methods efficiently. For example, prefer getChildDevices() over iterating through child devices directly.

  • Hubitat events: Handle events efficiently by avoiding unnecessary processing within event handlers. Consider using separate methods for complex logic.

  • Caching: Cache frequently accessed data to reduce redundant calculations and database calls. Utilize Hubitat's built-in caching mechanisms or external libraries like Guava Cache.

  • Asynchronous operations: Use asynchronous operations (runIn() or schedule()) for long-running tasks to avoid blocking the main thread and impacting responsiveness.

  • Logging: Use logging wisely. Excessive logging can impact performance. Log only critical information and consider using debug levels for troubleshooting.

ADDITIONAL TIPS

  • Code readability: While optimization is important, maintain clean and readable code for easier maintenance and future modifications.

  • Benchmarking: Measure the impact of your optimization efforts before and after to ensure they actually improve performance.

  • Community resources: Leverage the Hubitat community forum and resources for specific optimization tips and best practices.

Remember, optimization is an ongoing process. Continuously evaluate your code and adapt your techniques based on profiling results and changing requirements.

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That's awesome. Mind sharing the prompt you used? Would love to see how ChatGPT and Copilot respond as well.

For some reason, that particular prompt, even though it was my most Recent, is not listed. To the best of my recollection, I asked, almost verbatim:

"Suggest some coding techniques to improve the efficiency of my Device Driver files for Hubitat home automation controller, which are written in Groovy."

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Keep in mind that AI, at least as it currently exists, has a tendency to hallucinate, and a quick read of the above (I did not dive into every single point) is enough to see this:

Sounds like Java, but Groovy treats all primitive types as Objects, and I don't think the outcome would be any different. (I suppose some compiler optimizations may be possible if it knows boxing is never needed, but given the dynamic nature of the language, this may be difficult to know ahead of time, and I do know the internal workings of any.)

Good luck with this on the hub. :smiley:

Logging should have minimal impact on performance, at least at any sane level anyone would ever log at (obviously, making the computer do something impacts performance more than not making it do anything, but in practical terms this should not matter--and it's a great tool for debugging while you are writing an app or driver, though conventional options should be provided to end users if you want to fit in).

Back to the general subject, many apps and drivers are so small and so infrequently executed that optimization is unlikely to ever be a real concern if your code is otherwise well written. If you are, say, writing the webCoRE pistion executor, that's a different story. :smiley: But also maybe polling-based LAN drivers that are likely to run relatively frequently regardless of what actually happens, large apps or drivers for whatever reason, etc.

An easy thing, IMHO, most people can do for either efficiency or better error catching (if you don't actually need this behavior) is to use explicit types instead of def, whether for objects you're creating or as the return type (including void if none) for methods. That would be my first advice before most of the above. Then maybe start considering things like how to avoid storing large values in state if you don't really need them there, like if it's a large cached value (this is serialized to/from JSON on every execution). The point about needing to be able to actually read your code instead of it being merely "efficient" is, I think, also worth noting.

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I prefer “confidently incorrect” to “hallucination “. It will say things that are wrong but in a way that makes you want to agree with it. LLMs (“AI” is false advertising) are great assistants, but you can’t trust a single thing. You must verify whether it is correct or not.

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Agreed. I did appreciate how "confidently" it threw out this particular set of Hubitat-centric suggestions. Definitely provided food for thought, even if slightly off-base on a few points. I endeavor to author clean and lightweight code, so every little morsel helps.

I just plugged his recalled prompt into copilot and it came back with almost word for word the same thing. The first two sources cited were this community, I'm willing to bet this post.

Sometimes the responses are more consistent with an actual hallucination, e.g. referencing legal cases that don’t exist:

This happens in the medical field too.