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José Miguel Rojas

Publications and source records attributed to José Miguel Rojas.

4 recordsLinked to original sources

Accretion Disks in Schwarzschild-MOG and Kerr-MOG Backgrounds: MOG Parameter in terms of Observational Quantities

We apply a general relativistic framework to static and rotating black hole solutions in Scalar-Tensor-Vector Gravity or modified gravity (MOG). Our results yield exact analytic, closed-form relations expressing the mass $M$, the MOG coupling parameter $α$, and the distance $D$ of a Schwarzschild-MOG black hole in terms of a minimal set of directly measurable elements of the accretion disk: the total frequency shift, the telescope aperture angle, and the redshift rapidity. The resulting expressions are derived for particles close to the midline and line of sight, where the redshift rapidity is treated as a relativistic invariant encoding the evolution of the frequency shift with respect to the emitter's proper time in MOG spacetime. We further extend the formalism to the rotating Kerr-MOG geometry and obtain corresponding relations that determine the rotation parameter $a$ jointly with $M$, $α$, and $D$ on the midline. In the rotating background, we introduced the redshift acceleration (general-relativistic version of jerk) to disentangle the spacetime parameters. Crucially, the explicit appearance of $α$ in these formulas enables direct empirical estimation of this parameter, thereby providing a means to test for departures from standard general relativity. The present study focuses on the geodesic motion of massive test particles revolving around Schwarzschild and Kerr-MOG black holes, and the previous results obtained in the standard Schwarzschild and Kerr backgrounds are recovered in the limit $α\to 0$. The derived expressions are concise and suitable for incorporation into black hole parameter-estimation pipelines.

gr-qc↗

TestMiner: Software Testing Analysis for GitHub Repositories

Software systems have unique testing characteristics. Some projects can emphasize unit tests, while others may focus on end-to-end testing. Test organization may vary across ecosystems: in languages like Python and Java, tests are typically placed in dedicated folders, whereas Go and Rust projects commonly co-locate tests with source code. These distinctions make it harder to understand how a project approaches testing. In this paper, we present TestMiner, a tool for exploring software testing in GitHub repositories. TestMiner provides an overview of a project's testing practices, including test statistics, test location, test metrics across releases, and dependencies related to testing. We used TestMiner in an undergraduate Software Testing course, where 50 students explored the testing practices of real-world GitHub repositories. Overall, students expressed positive feedback regarding TestMiner. They were able to critically explore a variety of testing practices, including test organization, test evolution, test fixtures, mocking, and edge-case testing. TestMiner is available at: https://andrehora.github.io/testminer. Screencast: https://youtu.be/w1sBgLTq-7Y.

cs.SE↗

Automated Testing of Prevalent 3D User Interactions in Virtual Reality Applications

Virtual Reality (VR) technologies offer immersive user experiences across various domains, but present unique testing challenges compared to traditional software. Existing VR testing approaches enable scene navigation and interaction activation, but lack the ability to automatically synthesise realistic 3D user inputs (e.g, grab and trigger actions via hand-held controllers). Automated testing that generates and executes such input remains an unresolved challenge. Furthermore, existing metrics fail to robustly capture diverse interaction coverage. This paper addresses these gaps through four key contributions. First, we empirically identify four prevalent interaction types in nine open-source VR projects: fire, manipulate, socket, and custom. Second, we introduce the Interaction Flow Graph, a novel abstraction that systematically models 3D user interactions by identifying targets, actions, and conditions. Third, we construct XRBench3D, a benchmark comprising ten VR scenes that encompass 456 distinct user interactions for evaluating VR interaction testing. Finally, we present XRintTest, an automated testing approach that leverages this graph for dynamic scene exploration and interaction execution. Evaluation on XRBench3D shows that XRintTest achieves great effectiveness, reaching 93% coverage of fire, manipulate and socket interactions across all scenes, and performing 12x more effectively and 6x more efficiently than random exploration. Moreover, XRintTest can detect runtime exceptions and non-exception interaction issues, including subtle configuration defects. In addition, the Interaction Flow Graph can reveal potential interaction design smells that may compromise intended functionality and hinder testing performance for VR applications.

cs.SE↗

Software Testing for Extended Reality Applications: A Systematic Mapping Study

Extended Reality (XR) is an emerging technology spanning diverse application domains and offering immersive user experiences. However, its unique characteristics, such as six degrees of freedom interactions, present significant testing challenges distinct from traditional 2D GUI applications, demanding novel testing techniques to build high-quality XR applications. This paper presents the first systematic mapping study on software testing for XR applications. We selected 34 studies focusing on techniques and empirical approaches in XR software testing for detailed examination. The studies are classified and reviewed to address the current research landscape, test facets, and evaluation methodologies in the XR testing domain. Additionally, we provide a repository summarising the mapping study, including datasets and tools referenced in the selected studies, to support future research and practical applications. Our study highlights open challenges in XR testing and proposes actionable future research directions to address the gaps and advance the field of XR software testing.

cs.SE↗