Auflistung nach Autor:in "Makor, Lukas"
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- KonferenzbeitragHeap Evolution Analysis Using Tree Visualizations(Softwaretechnik-Trends Band 40, Heft 3, 2020) Weninger, Markus; Makor, Lukas; Mössenböck, HanspeterMemory anomalies such as memory leaks can dramatically impact application performance and can even lead to crashes. Thus, supporting developers in understanding the heap memory behavior of their systems is essential. Unfortunately, most memory analysis tools lack advanced visualizations that could facilitate developers in analyzing suspicious memory behavior. To analyze heap memory, it is common to group the heap’s objects, for example, by their types or by their allocation sites. Using multiple grouping criteria thus results in a tree-shaped representation of the heap content. Such a heap tree is then typically presented textually in a tree table. In this paper, we present ongoing research on using well-known tree visualization techniques to visualize such heap trees as well as their evolution over time. Such visualizations may ease the detection of proliferating heap objects, facilitating memory leak analysis. To demonstrate the feasibility and applicability of the presented approach, we implemented a web-based visualization tool and integrated it into AntTracks, our trace-based memory monitoring tool.
- KonferenzbeitragMemory Leak Visualization using Evolving Software Cities(Softwaretechnik-Trends Band 39, Heft 4, 2019) Weninger, Markus; Makor, Lukas; Mössenböck, HanspeterMemory leaks occur when no longer needed objects are unnecessarily kept alive. They can have a significant performance impact, possibly leading to a crash of the application in the worst case. Most state-of-the-art memory monitoring tools lack visualizations of memory growth over time. However, domains such as software evolution and program comprehension have shown that graphically visualizing the growth and evolution of a system can help users in understanding and interpreting this growth. In this paper, we present ongoing research on how to visualize an application’s memory evolution over time using the software city metaphor. While software cities are typically used to visualize static artifacts of a software system such as classes, we use them to visualize the dynamic memory behavior of an application. In our approach, heap objects can be grouped by arbitrary properties such as their types or their allocating threads. These groups are visualized as buildings arranged in districts, where the size of a building corresponds to the number of objects it represents. Continuously updating the city over time creates the feeling of an evolving city. Users can then identify and inspect those buildings, i.e., object groups, that grow the most. We integrated our approach into AntTracks, a trace-based memory monitoring tool developed by us, to prove its feasibility.