AISEJul 16

Alipay-PIBench: A Realistic Payment Integration Benchmark for Coding Agents

arXiv:2607.1457317.9
Predicted impact top 24% in AI · last 90 daysOriginality Synthesis-oriented
AI Analysis

This benchmark provides a controlled setting for diagnosing model capability and evaluating structured guidance in payment integration, a demanding repository-level software task.

Alipay-PIBench is a benchmark for evaluating coding agents on realistic payment integration tasks, containing 9 projects and 18 task instances. Under the with-skill condition, mean rubric pass rate (RPR) ranges from 68.58% to 91.37%, and access to a payment integration skill improves mean RPR by 10.31 percentage points on average.

Payment integration is a demanding repository-level software task: agents must select a suitable product, implement coordinated client-server flows, verify payment outcomes, and preserve consistency between transaction and business states. We introduce Alipay-PIBench, a benchmark for evaluating coding agents on realistic Alipay payment integration. It contains nine product-specific projects and 18 task instances, each organized into Basic functional-completion and Advanced risk-aware hardening scenarios. Scenario-specific rubrics support deterministic static, unit, integration, and end-to-end checks, supplemented by LLM-assisted assessment for semantic requirements. We evaluate six coding-agent models and report rubric pass rate (RPR). Under the with-skill condition, mean RPR ranges from 68.58% to 91.37%. Access to the alipay-payment-integration skill improves mean RPR by 10.31 percentage points on average relative to the without-skill condition, with gains varying across models, products, and scenarios. Method-level results distinguish source-level completion, executable payment behavior, and payment-domain requirements. Alipay-PIBench provides a controlled setting for diagnosing model capability and evaluating structured guidance in payment integration.

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