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<p>JPF is a model checking tool for java applications. JPF-core is the core structure of JPF. The build for jpf-core has been moved from ant (upto java 8 support version)to gradle. The current JPF-core version doesn’t have java 11 support i.e jpf-core is not portable for java 11. Jpf extensions have not moved from ant to gradle yet. This is because of the potential breaking changes from its previous versions. One such major breaking change in java 11 is “bootstrap methods”. The goal of this project is to fix gradle support for java 11, to update the extension template,provide the widely used jpf-extensions with gradle support.</p>
<p>JPF is a model checking tool for Java applications. It is a Virtual Machine (VM) for Java bytecode which executes the system under test (SUT). The JPF source is partially compatible with Java 11. The problem is to support new features of Java 11 like the bootstrap methods. They are used for things as common as string concatenation ( String + String, String + int, String + double, String + Byte, etc ). As of now, a few specialized cases are supported, but there are still few cases that fail with Java 11. There are also some internal APIs from Java 11 that no longer exist in Java 12. Therefore the aim of this project is to support the general case of bootstrap methods and update the code to support java 12.</p>
SQLancer is a tool that automatically tests DBMS in order to find bugs in their implementations. As of right now, SQLancer supports many great database systems, however, some of the systems are outdated including one of the most frequently used databases: PostgreSQL. SQLancer supports Postgre version 12 which became end-of-life in Nov 2024 and many versions along with critical changes have been made since then. This project aims to advance SQLancer to support the latest version of Postgres (version 17) by removing necessary deprecations as well as adding new features, by the end of this project, SQLancer will support additional features such as JSON data types/functions, procedural extensions, advance error handling, and hopefully reiterate the upgrade to other databases
<p>In recent years, ns-3 has been widely used for the simulation of wireless networks, because it features several built-in and external modules implementing different wireless technologies. The overall performance of this kind of networks are strongly influenced by the characteristics of the signal propagation through the wireless link, thereby, a proper modeling of the channel behavior is of primary importance to obtain reliable results from the simulations. This project aims to tackle this issue by proposing an extension of the spectrum module to model both frequency and spatial-dependent phenomena, and to account for the directional behavior of the signal propagation. This will be achieved by implementing the modeling framework described in 3GPP TR 38.901, which includes the statistical characterization of different propagation environments, supports the modeling of multi-antenna systems, and, thanks to its modularity, can be easily extended with new environments or other additional features. Even if it has been specifically designed for the simulation of cellular networks, it supports frequency bands between 0.5 and 100 GHz, thus can be used even for other wireless technologies.</p>
<p>In Data Science acquiring insight from data is what matters and any good data analysis tool must have the key functionalities required to extract information from data. Now, it’s needless to say how ubiquitous categorical data is in Data Analysis but they are not currently supported in Daru and operations on them like regression is not supported in Statsample and Statsample-glm. This shortcoming of Daru prevents data to be easily and to its full extent analyzed. This project aims to achieve just that.</p> <p>This project has broadly two goals:</p> <ul> <li>First is to efficiently store and manage categorical data in a Data Frame. This will be done with the help of a new data type CategoricalData and a class CategoricalIndex dedicated for this purpose. It also involves easy visualization of categorical data with help of plotting functionality.</li> <li>Next goal is to update various statistical analysis such as regression in Statsample and Statsample-glm taking categorical data into account.</li> </ul> <p>On accomplishing both of these tasks, one would be able to see Data more clearly.</p>
<p>Currently, the Google-Backend for GVfs supports only a subset of operations allowed by Google-Drive on the web-interface. The major problem with supporting all the operations is because of the difference in how POSIX systems handle files whereas how a database-backed system like Google-Drive handles files. This difference results into limitations as to what operations can be performed with the current libgdata API. Since, each file’s identifier is its ID, i.e. “name” equals ID, we have to specifically use “display-name” for storing a file’s title, which is what is shown by nautilus.</p> <p>Simply copying/moving files from one folder to other folder results into an error “Operation not supported” so as to preserve the file’s title. Copying/Moving is one of the fundamental operations that should be possible on a file. My ultimate goal with this proposal is to add support for this necessity and make the Google-Drive backend more usable.</p>
APNG (Animated PNG) is an animated format backwards compatible with PNG. It is supported by all the major browsers and has benefits over GIF such as partial transparency and support for more colors. The goal of this project is to integrate APNG support in LibreOffice, which had been requested for quite some time.
<p>Currently, there are no supports for S3 and GCS on Windows. It leads to two problems:</p> <ul> <li>The limitation of storage capacity and inconvenient of traditional hardware in contrast with cloud base storage.</li> <li>The overhead when using TensorFlow cross-platform as Linux and macOS have already been supported.</li> </ul> <p>Furthermore, according to this <a href="https://github.com/tensorflow/tensorflow/issues/19297" target="_blank">discussion</a>, @mihaimaruseac said that with the implementation of modular filesystem C API, the current S3, GCS and Hadoop support on Linux and MacOS will be moved out of TensorFlow, into SIG IO. New plugins will be necessary to ensure the continuous data accessibility.</p> <p>Therefore, this project aims to provide complete S3 and GCS support for Windows <strong>and</strong> write new plugins for S3,GCS and Hadoop for future use when the modular filesystem C API is ready.</p>
This project extends GNOME Crosswords' existing rendering facility to support printable puzzles with clues, and integrates printing support with crossword-specific options. It also has stretch goals, including broader puzzle support and an `ipuz2pdf` export utility.
In a single Knative Functions command, we aim to abstract the entire process of building serverless functions using WebAssembly (WASM)—from compiling the source code into WASM and containerizing it, to deploying it in Knative. This approach allows developers to focus solely on their source code, while Knative Functions handles all underlying transformations, ensuring seamless execution across various platforms. WebAssembly (WASM) significantly enhances performance, security, and flexibility. By compiling code written in languages such as C, C++, Rust, and Go into a bytecode format, WebAssembly ensures consistent execution across different processor architectures (x86, ARM, RISC-V). WASM’s fast execution and platform-independent bytecode format could expand the capabilities of Knative Functions, supporting a broader range of programming languages and processor architectures. Currently, there is no support for WASM in Knative Functions, which is why our project focused on pushing the boundaries of what’s possible by exploring WebAssembly support in Knative. During this project, we identified some limitations in fully integrating WASM into Knative Functions. However, by successfully implementing WASM support in Knative Serving, we were able to explore the potential of WASM within Knative and lay the groundwork for future improvements once these limitations are addressed.
This project aims to extend the existing Marine AR Module Builder into a more accessible, scalable, and educator-friendly toolkit for creating augmented reality learning experiences in Unity. The primary objective is to reduce the technical barrier for educators and developers by introducing intuitive editor tools, structured workflows, and reusable systems for building marine AR modules. The proposed system will include drag-and-drop environment upgradation, streamlined actor placement and configuration, and reusable behavior templates for movement, interaction, and ecological logic. To improve flexibility and maintainability, modules will support extensive JSON/script-based definitions, enabling structured and streamlined content creation. Validation tools will be implemented to detect missing assets, invalid configurations, and performance issues, ensuring reliability and usability.
<p>SymbiFlow does not currently support partial reconfiguration regions. Partial reconfiguration regions are crucial to ongoing FPGA research including reducing verilog to bitstream compilation times through separate compilation. Two major hurdles to the support of partial reconfiguration regions are SymbiFlow and VPR support for restricted placement/routing and the ability to generate and upload a partial bitstream. I will be taking on the first of these two hurdles.</p>
This project aims to add the Capitalization Handling Module for the es-pt language pair, as well as to create more rules expanding the tool. After that, capitalization will be moved to monolingual modules to improve system performance. As deliveries, will be done: 1. Uptate the language pair with the tool/ 2. Expansion in capitalization restoration/ 3. Documentation explaining how to use/ 3. Sets of tests ensuring the efficiency and opetarion of the capitalization handling module.
<p>The Kubernetes dashboard previously supported Third Party Resources (TPR), but these were replaced in Kubernetes by Custom Resource Definitions (CRD). As a result, the original TPR support was removed in Dashboard, but CRD support has not been added yet. This proposal aims at providing a generic support for Custom Resource Definitions to the dashboard, similar to the previous TPR support.</p>
<p>The Common Workflow Language (CWL) aims to standardize workflow languages to execute command line tools on the cloud and on local servers. Apache Taverna supports specific formats for import and export of workflows, but currently, CWL workflows are not fully supported. During the GSOC, we intend to provide structural import and export of CWL workflows. In addition, we intend to provide a way to support some of CWL command line tools inside Taverna and to export Taverna activities.</p>
<p>Drakvuf-sandbox is a malware analysis tool that is used to analyze the behavior of the malware in a contained environment. It uses the Drakvuf engine as its backend for interacting with the malware and abstracts a lot of stuff out making analyzing malware easy and user-friendly.</p> <p>Currently, Drakvuf-Sandbox only supports Windows-based Malware Analysis. The upstream Drakvuf also lacks the proper Linux support. Therefore, this proposal focuses on implementing the support for Linux-based malware analysis.</p>
<p>FHIR is a well known standard which rapidly gets popular among community. The purpose of this project is to expand the capabilities and functions of the OpenMRS FHIR module. OpenMRS has recently undertaken a commitment to implement FHIR in order to ensure better interoperability between healthcare systems. The OpenMRS FHIR module was developed as part of these efforts. FHIR specification is continuously subjecting to several development iterations which improves the usability. This project aiming to upgrade the FHIR module to newest version of standard.</p>
The Pocket Science Lab (PSLab) Android app currently offers a range of scientific instruments for on-the-go data collection and analysis. However, there's a pressing need to enhance the functionality of the oscilloscope feature and introduce support for new instruments, so that it attains equivalence to the dedicated devices. This proposal aims to address these issues by updating the oscilloscope module with advanced features and integrating support for additional instruments. The existing oscilloscope feature in the PSLab Android app lacks certain functionalities crucial for comprehensive data analysis, hindering users' ability to conduct precise experiments or measurements. Furthermore, the absence of support for new instruments limits the versatility of the app. To solve these challenges, a two-fold approach is proposed. Firstly, the oscilloscope will be updated to enhance waveform visualization, integrate automated measurements, and implement advanced triggering options. Secondly, support for new instruments will be implemented by identifying key scientific instruments, developing drivers and interfaces for seamless integration, and enhancing the user interface. Upon project completion, the deliverables will include enhanced oscilloscope functionality integration, smooth operation across all oscilloscope channels, implementation and calibration of designated sensors, integration and operation of other I2C compatible sensors, and comprehensive unit testing for all newly implemented features.
<p>This proposal considers performing modifications to the existing Operation Theater module to migrate it to the latest OpenMRS platform. The other main goal is to complete the workflow data capturing part along with scheduling to complete the OT module.</p> <p>It discusses</p> <ul> <li>the dependencies in migrating the module</li> <li>Data that needs to captured in operation theater workflows</li> <li>Running the scheduler automatically when the schedule is manually modified</li> <li>Generating reports related to the Operation theaters.</li> </ul>
<p>Project's main goal is adding new techniques and tools for text embedding modules in TensorFlow Hub.It is divided into three parts:</p> <ol> <li>Improve the TensorFlow Hub experience by creating demos and tools for exporting text embeddings to non-English languages (also in TF2),</li> <li>Release a proof of concept ULMFit (Universal Language Model Fine Tuning for Text Classification) module,</li> <li>Add a tool for showing how embedding changes after fine-tuning a module.</li> </ol>
<p>LibRoadrunner is a high-performance SBML based simulator for Systems and Synthetic Biology that uses LLVM to generate very efficient runtime code. SBML Arrays package is under development and provides support for expressing an array of components of a computational biological model. Arrays make it easier to represent large complex regular systems in a standard way. Currently, iBioSim is the only tool that supports SBML arrays. The goal of the project is to implement “SBML Array” support in libRoadRunner and ensure compatibility between libRoadRunner and iBioSim so that models can be exchanged correctly.</p>
MetaCall currently supports Linux (GCC), Windows (MSVC), and macOS but many platforms where developers want polyglot runtime support are missing.The core layers have partial support for some platforms but no CI, no environment script integration, and no testing to verify they actually work.Follow TDD approach: set up CI first , then fix environment script + build system, then fix test failures.I will go platform by platform for implementation.All platform logic lives in metacall-environment.sh there will be no hardcoded logic in CI YAML. 8 platform targets with CI pipelines with working environment script section, verified CMake detection and build, automated testing.Fixes to metacall/plthook fork for platforms that need it.
This project aims to add WebAssembly support to the Wild linker. Wild linker is a high-performance Linux linker written in Rust, and supporting the WebAssembly format would expand its applicability to even more Rust development scenarios. While LLVM's wasm-ld (lld) is currently the primary linker used for WebAssembly, Wild achieves link speeds that are often several times faster than lld for ELF linking across many scenarios, including mold, which was previously considered the fastest Linux linker. Since the fundamental linking process remains largely the same when adding WebAssembly support, much of the performance-critical implementation could be reused. Achieving similar performance gains for WebAssembly would therefore significantly reduce build times for Rust projects.
YCbCr is a color space used in video and digital systems to express color, where Y is the luma component and CB and CR are the blue-difference and red-difference chroma components respectively. This project aims to add YCbCr support to the Nouveau Vulkan driver (NVK), which opens the way for support for more applications and is also an important step towards Vulkan 1.1 compliance. Work on this project is split into 4 phases; first investigation and reading up the relevant parts of the Vulkan specification and the open-sourced NVIDIA hardware headers, second the actual implementation and coding, and finally the third and fourth stages being verification and review where I verify that the implementation is working and conformant, and fix any issues that pop up. All this would then be followed by a merge request implementing and enabling YCbCr support in the driver.