Browsing by Autor "Leonel Merino"

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    DGT-AR: Visualizing Code Dependencies in AR
    (2023) Dussan Freire-Pozo; Kevin Céspedes-Arancibia; Leonel Merino; Alison Fernandez-Blanco; Andrés Neyem; Juan Pablo Sandoval Alcocer
    Analyzing source code dependencies between components within a program is an essential activity in software development. While various software visualization tools have been proposed to aid in this activity, most are limited to desktop applications. As a result, the potential impact of augmented reality (AR) on improving dependency analysis remains largely unexplored. In this paper, we present DGT-AR, a node-link visualization tool for code dependencies in immersive augmented reality. DG T-AR extends the physical screen space of IDEs to the infinite virtual space. That is, developers neither have to sacrifice screen space nor leave the IDE and use third-party applications. We present the preliminary results of a pilot user study along with four key lessons learned. Additionally, we have made DGT-AR publicly available.
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    FlameGraph AR: Immersive Visualization of CPU Profiles in Augmented Reality
    (2025) Tiara Rojas-Stambuk; Luis Fernando Gil-Gareca; Juan Pablo Sandoval Alcocer; Leonel Merino; David Moreno-Lumbreras
    Performance analysis is essential to identify bottlenecks and improve software responsiveness. Flame graphs are widely used for this purpose, offering compact summaries of stack traces and execution times. However, as applications grow, flame graphs become large and dense, competing for space within IDEs already crowded with code editors and panels. We propose FlameGraph AR, a tool that offloads flame graph visualizations from the IDE to the physical environment using augmented reality. By integrating a Visual Studio Code extension with an AR application, developers can arrange interactive flame graphs on desks, walls, or in peripheral view. This immersive setup expands visualization space, supports gesturebased interaction, and enables parallel performance analysis without disrupting the coding flow.Video URL: https://vimeo.com/1089364433/e41cfa13c4
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    On the use of extended reality to support software development activities: A systematic literature review
    (Elsevier BV, 2025) Tiara Rojas-Stambuk; Juan Pablo Sandoval Alcocer; Leonel Merino; Andrés Neyem
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    Visualizing The Linux Kernel Performance with FlameGraph AR
    (2025) Tiara Rojas-Stambuk; Luis Fernando Gil-Gareca; Juan Pablo Sandoval Alcocer; Leonel Merino; David Moreno-Lumbreras
    In this challenge, we explore the evolution of the Linux kernel’s performance during compilation by comparing versions 5.19.17 and 6.14 through sampling-based CPU profiling. We collect profiling data using perf, transform into Chromecompatible .cpuprofile format, and analyze through a novel spatial visualization called FlameGraph AR.FlameGraph AR extends traditional flamegraphs beyond the limitations of IDE panels and conventional screens by rendering visualizations with augmented reality on a Microsoft HoloLens 2 device. By offloading the flamegraph to physical space, the FlameGraph AR tool enables developers to walk through wide and deeply nested call stacks, examine function frames through gesture-based interactions, and gain spatial awareness of the runtime behavior of a software system.In effect, we found immersive visualization especially valuable for analyzing architectural changes between the two kernel versions. We found that version 6.14 exhibits a significantly higher number of samples in several functions, such as native_write_msr, indicating intensified low-level CPU interactions. In addition, functions such as intel_pmu_enable_all and x86_pmu_enable also increased in frequency, suggesting increased reliance on performance monitoring. The stack depth analysis revealed that certain functions in version 6.14, including fpregs_assert_state_consistent and account_user_time, appear at significantly deeper levels than in earlier versions. Indeed, some reach the maximum stack trace depth of the profiling tool. The results indicate a growth in both modularity and the depth of instrumentation within the kernel execution paths.Multiple performance changes become visible and interactive with Flamegraph AR. For example, time-consuming functions show up as wide frames that span over desks or walls, and deep call stacks are explored physically by approaching or gazing upward. By mapping performance traces into the spatial domain, our tool provides a compelling method for understanding systemic evolution in large-scale software like the Linux kernel.Video URL: https://vimeo.com/1092935027/7d09676a83