Learning by doing means you spent a lot of time with reading documentation and exploring example code that illustrates the features of your favourite development toolchain. Getting a well-written example code has become substantially more difficult in the past years. Once upon a time, Google offered a search engine just for source code. It was active between 2006 and 2012. Now you are stuck with search engines and their deteriorating quality. The amount of AI-generated content, copy-&-paste from documentation, and hyperlinks to gigantic forum discussions filled with errors and even more copy-&-paste snippets destroys the classical Internet research. You have to select your sources carefully. So what is a good strategy here? I have compiled a short checklist that enables you to avoid wasting time.
- Start with the tutorials and documentation of your development tools/languages. Some have sections with examples and a well-written explanation. It depends on the developers, because writing didactically valuable explanations takes some effort.
- Actively look for content from schools, colleges, or universities. Sometimes courses are online and contain the information you need. Try to prefer this source category.
- When using search engines, keep the following in mind:
- Skip results pushed by Search Engine Optimization (SEO); SEO is basically a way to push results to the top by adding noise and following the search engine company’s policy of the day. You can recognise this content by summary texts that don’t tell you the facts in briefs, the obnoxious Top N phrase in the title, and even more variations of copy-&-paste text fragments.
- Do not „AI-enhance“ the results! While Large Language Model (LLM) algorithms may have used actual sources relevant to your research during training, their results are merely a statistical remix subtly altered by hallucinations. Go directly to software/coding forums and look for relevant threads. LLM-generated code will contain more bugs or bugs more frequently.
- Do not use content sponsored by companies pushing their development products. Research is all about good examples, good explanations, and facts, not marketing.
- Mind the date of the results. AI spammers and companies following the AI hype have changed dates of published articles to sell them as new or updated. Don’t fall for that.
- Inspect secure coding standards and policy documents. Some contain useful sections with examples. You can also verify the search results with this by recognising outdated advice (deprecated algorithms, old standards, etc.).
- Inspect version control repositories and look for example code. A lot of projects have samples and test code that is part of the release.
- Write your own test code and explore! Add the created test code to your personal/project toolbox. You can later turn this code into unit tests or use it to check if major version changes broke something.
Unfortunately, these hints won’t change the degrading quality of the current search engines. It will help you filter out the noise.