BewareMyPower commented on PR #25928: URL: https://github.com/apache/pulsar/pull/25928#issuecomment-4619846092
From a previous conversation with Gemini: <html><head></head><body><p data-path-to-node="0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">It’s a common quirk that can make AI-generated code look a bit "clunky" compared to how a human would write it. While you might prefer a clean <code data-path-to-node="0" data-index-in-node="143" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">import</code> statement at the top, AI agents often default to <b data-path-to-node="0" data-index-in-node="199" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">Fully Qualified Class Names (FQCN)</b> for several practical and technical reasons.</p><p data-path-to-node="1" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !import ant;">Here is why your AI "coworker" is being so verbose:</p><h3 data-path-to-node="2" style="font-family: "Google Sans", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">1. Avoiding Naming Collisions</h3><p data-path-to-node="3" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">AI models are trained on massive datasets where multiple libraries might have classes with the same name. For example, there are many different <code data-path-to-node="3" data-index-in-node="144" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">Configuration</code>, <code data-path-to-node="3" data-index-in-node="159" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">Context</code>, or <code data-path-to-node="3" data-inde x-in-node="171" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">Action</code> classes across various Java frameworks.</p><ul data-path-to-node="4" style="padding-inline-start: 32px; font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><li style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><p data-path-to-node="4,0,0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">By using the FQCN (like <code data-path-to-node="4,0,0" data-index-in-node="24" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">org.apache.pulsar.common.policies.data.AuthAction</code>), the AI ensures the code is <b data-pat h-to-node="4,0,0" data-index-in-node="103" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">unambiguous</b>.</p></li><li style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><p data-path-to-node="4,1,0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">It eliminates the risk of the compiler getting confused if two imported packages contain the same class name.</p></li></ul><h3 data-path-to-node="5" style="font-family: "Google Sans", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">2. Contextual Independence</h3><p data-path-to-node="6" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">When an AI generates a snippet of co de, it often treats that block as a standalone unit.</p><ul data-path-to-node="7" style="padding-inline-start: 32px; font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><li style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><p data-path-to-node="7,0,0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><b data-path-to-node="7,0,0" data-index-in-node="0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">The "Headless" Problem:</b> Often, the AI provides the logic (the method body) without generating the entire file structure (package declaration and imports).</p></li><li style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><p data-path-to-node="7,1,0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">By using the full path, the code becomes "plug-and-play." You can paste it into an existing file, and it will work immediately without you having to manually resolve imports or scroll to the top of your IDE.</p></li></ul><h3 data-path-to-node="8" style="font-family: "Google Sans", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">3. Training Data Bias</h3><p data-path-to-node="9" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">A significant portion of AI training data comes from:</p><ul data-path-to-node="10" style="padding-inline-start: 32px; font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><li st yle="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><p data-path-to-node="10,0,0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><b data-path-to-node="10,0,0" data-index-in-node="0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">Stack Overflow snippets:</b> Where users often use FQCNs to show exactly which library they are using.</p></li><li style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><p data-path-to-node="10,1,0" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;"><b data-path-to-node="10,1,0" data-index-in-node="0" style="font-family: "Google Sans Text", sans-ser if !important; line-height: 1.15 !important; margin-top: 0px !important;">Machine-generated code/Protobufs:</b> Auto-generated Java code (like that produced by gRPC or Thrift) frequently uses full paths to avoid errors, and the AI mirrors this pattern.</p></li></ul><h3 data-path-to-node="11" style="font-family: "Google Sans", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">4. Deterministic Reliability</h3><p data-path-to-node="12" style="font-family: "Google Sans Text", sans-serif !important; line-height: 1.15 !important; margin-top: 0px !important;">In the "mind" of an LLM, being explicit is safer than being implicit. If it writes an import statement at the top but then forgets to use it, or uses a different version in the code, the code fails. Using the full name directly at the call site is a "fail-safe" way to ensure the code compiles on the first try.</p> -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
