Author

Rui-Xuan Ying

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Review Sep 2026

Test-Driven Approaches to Software Engineering with Large Language Models: A Survey of Phases, Tasks, and Agent Skills

A structured scoping survey organized around the question of what decision a test changes is presented, and distinguishes the Red--Green--Refactor cycle from test-conditioned generation, execution-guided refinement, test-mediated analysis, and evaluation-only testing.

Yun-Hao Liang, Cheng-Guang Gan, Rui-Xuan Ying et al. · 0 citations

Preprint Sep 2026

Correct Tests Are Not Enough: Measuring and Training Oracle Conversion in Specification-Based Test Generation

Generating tests from a natural-language specification requires both an input that exposes faulty behavior and a correct expected output. These requirements need not improve together: a model can increase test correctness by choosing easier inputs, or discover useful inputs whose expected outputs it cannot predict. We...

Yun-Hao Liang, Cheng-Guang Gan, Rui-Xuan Ying et al. · 0 citations

Preprint Jul 2026

Do Code Language Models Follow Tests? Paired Interventions on Program Behavior

This work studies test utilization through matched prompting controls, paired semantic interventions, and test suites selected by fault detection to make test-specified rule changes measurable alongside implementation capability and benchmark correctness.

Yun-Hao Liang, Cheng-Guang Gan, Rui-Xuan Ying et al. · 1 citation

Preprint Jul 2026

Do Code Language Models Use Tests? A Behavioral and Representational Study of Test-Driven Code Generation

Public tests are widely used to guide large language model code generation, but whether models treat them as executable specifications or merely as extra prompt context remains unclear. We study test-driven code generation on HumanEval+, MBPP+, and recent LiveCodeBench tasks using Qwen2.5-Coder-7B and Qwen3.6-27B. We c...

Yunhao Liang, Chengguang Gan, Ruixuan Ying et al. · 0 citations

Preprint Aug 2026

Security Tests as Executable Specifications for LLM Code Generation: Benefits, Trade-offs, and Coverage Limits

The results show that executable feedback can repair secure-code generation, but its benefits depend on the model, task, feedback entry point, and especially test coverage.

Yun-Hao Liang, Cheng-Guang Gan, Rui-Xuan Ying et al. · 1 citation

#software testing Preprint Aug 2026

Auditing and Decomposing Feedback-Driven Evolution in LLM Test Generation under the Oracle Problem

An audit-and-placebo protocol is proposed that separates verifier artifacts, interaction scaffolding, and grounded feedback credit in evaluations of self-evolving test generators in evaluations of self-evolving test generators.

Yunhao Liang, Chengguang Gan, Ruixuan Ying et al. · 0 citations