Repairing Leaks in Resource Wrappers

• URL: http://arxiv.org/abs/2510.03461v1
• Date: Fri, 03 Oct 2025 19:34:19 GMT
• Title: Repairing Leaks in Resource Wrappers
• Authors: Sanjay Malakar, Michael D. Ernst, Martin Kellogg, Manu Sridharan,
• Abstract summary: This paper makes four key contributions to improve resource leak repair in the presence of wrappers.<n>It integrates inference of resource management specifications into the repair pipeline.<n>It makes detection tools report problems closer to the root cause, often in a client of a resource wrapper rather than within the wrapper class itself.
• Score: 2.359867155288065
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: A resource leak occurs when a program fails to release a finite resource like a socket, file descriptor or database connection. While sound static analysis tools can detect all leaks, automatically repairing them remains challenging. Prior work took the output of a detection tool and attempted to repair only leaks from a hard-coded list of library resource types. That approach limits the scope of repairable leaks: real-world code uses resource wrappers that store a resource in a field and must themselves be closed. This paper makes four key contributions to improve resource leak repair in the presence of wrappers. (1) It integrates inference of resource management specifications into the repair pipeline, enabling extant fixing approaches to reason about wrappers. (2) It transforms programs into variants that are easier to analyze, making inference, detection, and fixing tools more effective; for instance, it makes detection tools report problems closer to the root cause, often in a client of a resource wrapper rather than within the wrapper class itself. (3) A novel field containment analysis reasons about resource lifetimes, enabling repair of more leaks involving resources stored in fields. (4) It introduces a new repair pattern and more precise reasoning to better handle resources stored in non-final fields. Prior work fixed 41% of resource leak warnings in the NJR benchmark suite; our implementation Arodnap fixes 68%.

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