TL;DR
VeriScale is a framework that enhances code generation benchmarks by creating diverse, challenging test cases through adversarial methods, revealing model weaknesses and improving evaluation accuracy.
Contribution
It introduces a novel adversarial test-suite scaling framework, instantiated as VerinaPlus and VerinaLite, to improve the quality and discriminative power of code verification benchmarks.
Findings
VerinaPlus expands test suites by over 83 times, exposing model weaknesses.
Models show sharp score drops on enhanced benchmarks, indicating improved evaluation sensitivity.
VerinaLite maintains discriminative power with reduced evaluation cost.
Abstract
As large language models (LLMs) are increasingly deployed for software engineering, constructing high-quality benchmarks is crucial for evaluating not just the functional correctness, but also the formal verifiability of generated code. However, existing benchmarks are limited by the quantity and quality of positive and negative test cases, leading to an overestimation of model capabilities in generating specifications and implementations. To address this, we propose VeriScale, a novel framework driven by the adversarial implementations. It consists of two stages: test-suite expansion to construct diverse and challenging test cases, and test-suite reduction to distill them into compact yet discriminative suites. While VeriScale is general, we instantiate it on Verina to construct VerinaPlus, which expands the original test suites by over 83, and VerinaLite, a lightweight…
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