Who Ate My Memory? Towards Attribution in Memory Management
Gunnar Kudrjavets (University of Groningen), Ayushi Rastogi, (University of Groningen), Jeff Thomas (Meta Platforms, Inc.), Nachiappan, Nagappan (Meta Platforms, Inc.)

TL;DR
This paper discusses the need for lightweight, detailed memory attribution tools for deployed applications, addressing current limitations in profiling methods that hinder debugging and performance optimization.
Contribution
It highlights the importance of developing practical memory attribution techniques suitable for production environments, and reviews early-stage research in this area.
Findings
Current profiling tools are impractical for production use.
Developers lack granular memory usage data in deployed applications.
Research into memory attribution data structures and techniques is emerging.
Abstract
To understand applications' memory usage details, engineers use instrumented builds and profiling tools. Both approaches are impractical for use in production environments or deployed mobile applications. As a result, developers can gather only high-level memory-related statistics for deployed software. In our experience, the lack of granular field data makes fixing performance and reliability-related defects complex and time-consuming. The software industry needs lightweight solutions to collect detailed data about applications' memory usage to increase developer productivity. Current research into memory attribution-related data structures, techniques, and tools is in the early stages and enables several new research avenues.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSoftware System Performance and Reliability · Software Engineering Research · Web Data Mining and Analysis
