Heap Patterns for Memory Graph Visualization

Abstract

Visualizing large memory graphs containing dynamic data structures and nested payload data is crucial when debugging legacy and modern software. However, existing visualization tools primarily focus on aggregating data structures and either rely on hard-coded patterns, generic heuristics, or predicates written in expressive logics. We present a novel heap pattern language for concisely and intuitively describing structural aspects of dynamic data structures and nested payload data. Evaluating a heap pattern on a memory graph yields a set of matching groups of interconnected objects, and analyzing these groups enables the construction of a multi-level hierarchy for memory graph visualization, where groups can individually be (un)folded to the desired level of detail. We have prototypically implemented our heap pattern language in the Memory Graph Explorer tool and illustrate its use for visualizing large memory graphs on real-world and textbook examples. Unlike existing tools, developers can now control the construction of hierarchies using heap patterns to flexibly and locally adjust the level of memory graph abstraction in an interactive graph visualization to highlight the areas demanding attention during debugging.