Use these structured prompting techniques to improve the quality and usefulness of AI output in testing workflows ...

Tenzai’s tests suggest that current vibe coding does not provide perfect coding. In particular, it requires very detailed and ...

Learn how to use GitHub Copilot to generate code, optimize code, fix bugs, and create unit tests, right from within your IDE ...

Avoid these mistakes to build automation that survives UI changes, validates outcomes properly, and provides useful feedback.

The new science of “emergent misalignment” explores how PG-13 training data — insecure code, superstitious numbers or even extreme-sports advice — can open the door to AI’s dark side. There should ...

Creating a self-healing code agent is a fantastic approach to enhancing the quality and reliability of code generated by language model (LM)-based agents. Have you ever been frustrated by buggy, ...

The official repository which contains the code and pre-trained models/datasets for our paper Efficient Test-Time Scaling via Self-Calibration. As shown in the previous figure, our approaches can ...

This study presents an Acceptability Judgment Task (AJT) conducted with Latinx 1 Spanish-English bilinguals in the United States. We take a social approach to the AJT by contextualizing code-switching ...

Abstract: Adversarial code examples are important to investigate the robustness of deep code models. Existing work on adversarial code example generation has shown promising results yet still falls ...

Abstract: Flaky tests are problematic because they non-deterministically pass or fail for the same software version under test, causing confusion and wasting development effort. While machine learning ...