What is it about?
HeapLens is an open-source tool that helps developers investigate why Java applications use too much memory. It works inside Visual Studio Code and compatible editors such as Cursor, Antigravity etc. Developers open a “heap dump,” a snapshot of a program’s memory, and explore which objects occupy space and what keeps them from being released. HeapLens helps identify suspected leaks, find duplicated data, compare memory snapshots over time, and navigate from findings to available source code. Developers can also search the snapshot using a query language and generate reports to share with their team. An optional AI assistant helps explain findings and suggest further investigations. The memory analysis runs locally; using AI can send selected information to the configured model service.
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Why is it important?
Knowing that an application uses too much memory is only the beginning. Developers need to understand what is being retained, why it remains in memory, and which code deserves attention. HeapLens connects these steps within the workspace where developers already write and debug their applications. It combines visual exploration, targeted queries, source navigation and optional AI assistance, helping developers follow the evidence without repeatedly moving between separate tools. Comparing snapshots also helps teams investigate memory growth and assess changes after a proposed fix. As an open-source project, HeapLens makes its implementation available for inspection, experimentation and improvement.
Perspectives
My goal with HeapLens is to make memory investigation a more approachable part of everyday software development. I want developers to move from “What is using all this memory?” to “Which code should I investigate?” while keeping the evidence in view. The tool has continued to evolve since this paper was prepared. Recent work has focused on improving memory calculations, recovering from analysis failures, and giving users clearer control over information shared with AI services. I see AI as an assistant, not a substitute for engineering judgment. My hope is that developers will use HeapLens, challenge its limitations, and help shape its continued development.
Sachin Gupta
Read the Original
This page is a summary of: HeapLens: An IDE-Integrated Tool for Heap Dump Analysis with In-Editor Source Bridging and LLM-Assisted Diagnosis, October 2026, ACM (Association for Computing Machinery),
DOI: 10.1145/3837729.3840479.
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