All posts tagged with "AI" from the Software Engineering Laboratory.
Learn how to use LLMs like Claude, Gemini, and local models to generate, explain, refactor, and extend PHP code. Covers three real-world coding workflows, prompting patterns, responsible-use guardrails (hallucination checks, security review, licensing), and a hands-on exercise with runnable PHP code.
Read more →Learn how to use LLMs and AI-assisted workflows to turn vague stakeholder requests into structured user stories, SRS snippets, and acceptance criteria. Covers prompt engineering for requirements, a complete PHP helper to call LLM APIs, traceability mapping, and the limitations of AI-generated requirements — including hallucinations and bias.
Read more →Learn how to build a bug prediction classifier using PHP—from extracting code metrics (LOC, cyclomatic complexity, change churn) to training and evaluating a Naive Bayes model that identifies high-risk modules before they break.
Read more →Learn how to use LLMs to generate, maintain, and validate API documentation, README files, inline comments, and changelogs for PHP/Laravel projects. Covers Scribe, PHPDoc, MkDocs, and custom LLM pipelines with a human-in-the-loop review workflow — and shows where LLMs fail and hallucinate.
Read more →A seminar exploring how AI tools are transforming software testing workflows. Learn about automated test generation, bug prediction, and quality analysis from SE Lab researchers.
Read more →Learn how to use AI coding assistants to generate, review, and refine PHPUnit tests. Covers practical workflows with PHP examples, common AI pitfalls (hallucinations, brittle tests, missing edge cases), and when AI-assisted test generation helps — and when it fails.
Read more →// Jurusan Teknologi Informasi, Politeknik Negeri Malang
"address": "Jl. Soekarno Hatta No.9, Jatimulyo, Kec. Lowokwaru, Malang, East Java — Indonesia 65141"
"email": "imam.fahrur@polinema.ac.id"