[XSL-LIST Mailing List Archive Home] [By Thread] [By Date] [Recent Entries] [Reply To This Message] bad code Re: Subject: ChatGPT results are "subject to
Hi all, it did not take much investigation to find that there was an invalidity in the XSLT that was "stupid" (a misplaced attribute constructor after a child element constructor in a template), and there were various other things that I improved to get it to produce the same result as my own XSLT 2 transform that I used for comparison. So at this time, our concern will be for the people who are just starting out and don't yet understand why the XSLT is wrong and/or how to fix it. The more expert of you (I am only middling fair at XSLT) will want to make your own test cases. My guess is that the more interesting your input and output and prompts are, the more you will have to draw on your expertise to decide if the ChatGPT result is correct. The speed of the results is what is helpful. If you are poking at a solution bit by bit, you might be able to get some useful code results quickly to test as you develop. But from what I understand, and what I experienced myself, writing a good prompt is a science of its own (well-suited for a number of you experts in the list). In a way, it walks me back mentally to the development state of requirements gathering. What is the source content? What do I need to produce for the client? How can I test my result meets the requirement? It seems like writing the test cases can also be automated (as I mentioned, I asked ChatGPT to generate a schematron and an Xspec). I would be interested in your thoughts about whether using ChatGPT will work better for a procedural language or a declarative language. (You can ask ChatGPT to return the generated code in other languages than XSLT. From what I see in the list of ChatGPT Code languages, it wasn't specifically trained on XSLT, so someone who builds their own training set will get better results. You folks probably have the best training examples in the world in the xsl-list.) I don't think there's any going back, so the chances of people creating code that won't run, that they can't debug themselves and which ChatGPT may not provide the correction required if prompted, is high. Michael, I wonder what "nasty accidents" you are thinking of -- some XSLTs used in particular industries with real-world safety issues? Maybe we can start to create some advice for clients on QA and testing protocols. - Dorothy
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