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Sapienz 获 ISSTA 2026 最具影响力论文奖
Meta 工程博客宣布，Ke Mao、Mark Harman 与 Yue Jia 的 2016 年论文《Sapienz: multi-objective automated testing for Android applications》获得 ACM SIGSOFT ISSTA 2026 最具影响力论文奖。Sapienz 通过多目标探索自动测试 Android 应用，在 1000 个 Google Play 热门应用评估中发现 558 个此前未知崩溃，并帮助工程师以更少步骤复现问题。论文发表后 17 个月内即在 Meta 规模化部署，目前每天运行数百万次测试、每周暴露数千个唯一崩溃，并支撑每月数百个应用发布；其探索引擎还被用于 WhatsApp 的动态污点分析。Meta 在 ISSTA 2026 keynote 中提出，LLM Agent 可将自动化测试从可靠性扩展到功能正确性与自动修复。
AI推荐理由 Meta 官方工程博客，信息密度高且事实明确：Sapienz 获 ISSTA 2026 最具影响力论文奖，并给出可验证的落地数据（在 1000 个 Google Play 应用中找出 558 个此前未知崩溃；发表后 17 个月内在 Meta 规模化部署，如今每天运行数百万次测试、每周发现数千个唯一崩溃）。局限在于这是回顾性获奖公告，核心方法（多目标自动化测试）本身并非新进展；文中关于 LLM Agent 扩展到功能正确性与自动修复的表述属于 keynote 展望，未提供具体证据。
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Ke Mao, Mark Harman, and Yue Jia have been recognized with the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2026 Most Influential Paper Award for their 2016 research, “Sapienz: multi-objective automated testing for Android applications.” The recognition celebrates a decade of impact from work that began at University College London and went on to become testing infrastructure at Meta. Sapienz automatically tests apps to find crashes and helps engineers reproduce them in fewer steps, making failures easier to investigate. The original research combined three goals: exploring more of an app, finding more crashes, and reducing the number of steps needed to trigger them. In its evaluation on 1,000 popular Google Play apps, Sapienz found 558 previously unknown crashes. Within 17 months of publication, Sapienz was deployed at scale at Meta. Today, it runs millions of tests daily across Meta’s platforms, surfaces thousands of unique crashes each week, and helps safeguard hundreds of app releases each month, supporting product reliability and quality. Sapienz’s applications quickly expanded beyond crash detection. By using test accounts with synthetic conversations, it became the app-exploration engine for dynamic taint analysis at WhatsApp. We shared Sapienz’s journey in October in our ISSTA 2026 keynote delivered by Ke Mao, “Finding the Bugs Users Would Find: From Sapienz to Autonomous Agents.” Beyond detecting crashes, large language model (LLM) agents can now explore apps and reason about whether their behavior matches what users should expect, extending automated testing from reliability to functional correctness and, increasingly, automated repair. Sapienz’s core ideas of multi-objective exploration and actionable fault revelation carry over directly. A decade on, those founding principles still hold true. As part of Meta’s overall privacy and risk management program, this work reflects our ongoing efforts to ensure privacy considerations are at the heart of our product development process, helping teams identify risks earlier in the development lifecycle, apply safeguards more consistently, and build privacy protections into each new innovation from the start. The post Sapienz Receives ISSTA 2026 Impact Paper Award appeared first on Engineering at Meta.