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This project focuses on implementing the backend API for managing Binding Policies. The API should support creating, reading, updating, and deleting policies while ensuring robust validation and performance. Objectives - Develop backend API endpoints for Binding Policy management. - Ensure proper validation and enforcement of Kubernetes standards. - Optimize backend performance for handling multiple policy requests. - Implement logging and error handling for better debugging. Expected Outcomes - A secure and scalable backend API for Binding Policies. - Full CRUD functionality accessible from the UI. - Improved validation and performance optimizations.

<p>The custom element API allows javascript authors to create reusable web components. The author can create custom element constructors and setup callbacks for when various reactions occur on the element such as when its attributes are mutated. While this was possible in the past with non-standard elements, this API allows authors to have more functionality and ensures that these custom elements will not be broken by future changes to the web platform. While this is a new API, new web frameworks such as A-Frame and Polymer are built using custom elements. As the usage of custom elements increases, it will be important that Servo supports this API.</p>

<p>Currently Thunderbird uses mbox as primary storage format for mails (locally). All the mails in a folder are stored in the same file with the same name as the folder and no extension. The messages are separated from each other by a "From - " line. The maildir format is also supported, but there is no converter for it yet. The goal is to implement a component to migrate a store from the mbox format to maildir format. In order to achieve the goal a new store should be created and all the messages from all the folders of the old store should be moved to respective folders of the new store in maildir format. The folder hierarchy of the old store needs to be maintained in the new store. The message copying should be carried out in a worker using OS.File to prevent other tasks from getting locked up for long.</p>

Jaeger is a widely used distributed tracing platform. This project aims to integrate Small Language Models (SLMs) and Large Language Models (LLMs) into the Jaeger ecosystem to provide intelligent trace analysis. Key features include natural language search mapping (mapping English queries to Jaeger's internal search parameters), contextual analysis, and summarization ("Explain this Span" or "Explain this trace"). The project involves backend integration using Go and LangChainGo, and frontend integration within the Jaeger React UI. Expected Outcome: A working "Natural Language Search" input that populates the Jaeger search form, contextual "Explain" buttons for errors and spans, a robust backend implementation using langchaingo supporting local models (e.g., Ollama) via YAML config, and comprehensive documentation.

<p>At present, the Kthena router provides robust support for routing within the cluster. However, during discussions with customers, some users have expressed a need for the ability to integrate with external large language model APIs. Consequently, the Kthena community plans to use this LFX to enable the router to access third-party LLM APIs.</p><p><br></p><p>Expected OUtcome:</p><p>&nbsp;1. Proposal</p><p>&nbsp;2. Code(Include unit test. It would be even better if end-to-end testing were included. However, external LLM APIs are unlikely to offer stable, long-term free access, so end-to-end testing is not a prerequisite.)</p><p>&nbsp;3. User Guide and related documents.</p><p><br></p>

We want to discuss, map out, and plan a Next Generation Arithmetic (to include complex numbers) extension or equivalent to the RISC-V spec. This was discussed on the tech list a couple of years ago. We think there is a strong demand for this facility right now. The results of this work, likely including a feasibility study and code snippets, will inform the community on how to integrate NGA formats, including posits, into a RISC-V implementation. This internship will include our Journal Club approach where all interns will get opportunities to incorporate their additions and review the appropriate papers. To further these goals, and to give a reference to the substantial performance, accuracy and reproducibility advantages of NGA-enhanced RISC-V, a large number of CPU-based codes will be refactored to take advantages of the best parts of the appropriate arithmetic approaches while keeping floating-point options open.

<p>Cwltool is a reference implementation of the Common Workflow Language. It provides comprehensive validation of CWL files and include tools related to working with CWL.<br> CWL is a specification which is used to describe command line tools and workflows, providing benefits like flexibility, scalability and portability.<br> Currently cwltool is developed for Linux and OS X and not for Windows Operating System.<br> Also, cwltool and schema-salad targets python 2.7.</p> <p>The aim of this proposal is to enhance cross platform compatibility and usability of cwltool and schema-salad by:</p> <ul> <li><strong>Migrating to complete Python2+3 support for cwltool and schema-salad.</strong></li> <li><strong>Extending cwltool support to Microsoft Windows Operating System.</strong></li> </ul>

Performance benchmarking distributed systems (such as DLTs) is a challenging task, comprising of multiple aspects, such as scalable workload generation, representative workload definitions, and comprehensive data analysis. Hyperledger Caliper is a general-purpose benchmarking tool with the goal of mitigating the aforementioned aspects of performance benchmarking: 1. It provides a flexible architecture to allow scalable workload generation. 2. It collects and reports results based on detailed client-observable execution traces. 3. It allows the implementation/plug-in of custom workload behaviors to meet the diverse criteria of a wide range of business scenarios. The flexible support of the aforementioned performance benchmarking aspects inherently makes the setup and configuration of a Caliper-based project cumbersome and error-prone: - The user must provide information about the system under test (SUT) in the form of a network configuration file. - The user must also specify the flow of the benchmark run in the form of a benchmark configuration file. - The runtime behavior of Caliper components can be influenced in detail through a configuration file. - As with most programming-related projects, a Caliper-based project should employ best practices to make its structure flexible and maintainable. The goal of the mentorship project is to deliver a Visual Studio Code extension that can help users perform the aforementioned tasks in an assisted and possibly automated manner.

<p>Servo has support for Web Workers, and the new Fetch Api whose development is in progress is another new standard, that aims to replace XMLHttpRequest (XHR), and provides a cleaner api for anything involving requests and responses.The Fetch api spec also has a subsection which details on handling fetch calls within a service worker context. <a href="https://slightlyoff.github.io/ServiceWorker/spec/service_worker/" target="_blank">Spec</a> Service Workers are the new standard, for modern web apps, which aims to bring native app like experience to browser based apps, by providing a programmable api, for caching certain paths of pages, ,manipulating routing within an application,intercepting network requests according to user logic.</p> <p>Servo has a partial implementation of Fetch api, but the Service Worker api’s are currently missing and if implemented, Servo will be able to intercept network calls made from within the Service Worker’s context, the “handle_fetch” subsection of the Fetch Spec, is to be implemented. <a href="https://fetch.spec.whatwg.org/" target="_blank">Spec</a></p> <p>My project is to have a partial implementation of the new Service Worker Api and its helper interfaces, in Servo. The project is focused on working on parts of the Service Worker Specification which revolves around intercepting network requests.</p>

The initial interaction for many users with a project often begins with its "Quick Start" guide. Ensuring this guide is of high quality and up-to-date is crucial. Currently, the community offers several quick start methods, including a one-click setup script (hack/local-up-karmada.sh), installation tools such as Helm, karmadactl, and the operator, alongside learning tutorials on Killercoda. Although the community's CI effectively maintains these installation methods, it lacks support for different operating systems, notably macOS. Furthermore, some Killercoda tutorials are outdated and do not reflect the latest features and best practices. This project aims to ease the entry barrier for new users by enhancing the quick start process, ensuring cross-platform compatibility, and updating educational content. Expected Outcome: 1. Verify the feasibility of installing hack/local-up-karmada.sh on macOS environments, including both macOS ARM and Intel and address any issues that arise. 2. Implement a new CI workflow in GitHub Actions to test Karmada's installation and basic functionalities on macOS. GitHub Actions can select specific environments through runs-on, covering both macOS ARM and Intel. 3. Revise existing outdated scenarios on Killercoda and develop valuable new scenarios to guide users through current features. This includes: *Extracting common functions from various scenarios to reduce code duplication......

<p>The 3D structures of protein and organic molecules are tough to understand since not all can visualize their structures in the mind. The project aims to build a <strong>real-time</strong> web application using socket programming(just like in online multiplayer games) that shall facilitate an active learning environment to visualize and learn the functions of each component in the 3D structure. This one of a kind software that brings in the best of online multiplayer gaming and virtual labs will be used by teachers, students, and researchers all across the world.</p>

<p>The Syft ecosystem allows one to write software that can compute over information you do not own on machines you do not have (total) control over. PySyft mainly allows <strong>direct computation on unseen data</strong> and generates static graphs of computation that can be deployed or scaled later.</p> <p>To do so PySyft creates an AST that maps function calls to their exact path and knows what to do with a node in the tree. AST allows remote execution, and to do so AST provides a local handler for the result of remote execution through pointer alongside generating all the permitted methods and attributes on a Pointer.</p> <p>The current implementation has integration for pandas’ DataFrame and Series, i.e, one can <strong>remotely execute methods and access attributes</strong> on objects on these classes using their pointers. This is to be <strong>further extended for all the classes and global functions in pandas</strong>.</p>

This project aims to complete and modernize the React-based UI of FOSSology by aligning it with the updated REST API v2 and current frontend best practices. The work includes finalizing the incomplete interface, upgrading React to 19.1.0 for improved performance and concurrency, and migrating from yarn to pnpm for faster, space-efficient development. It will also implement UX improvements from the FOSSology UX and UI redesign project and create a reusable component library with Storybook. Comprehensive documentation and deployment guidelines will be provided to ensure long-term maintainability and contributor onboarding.

<p>The goal is to implement a wrapper (common interface) for the identification algorithms’ logic in MSDK (that will allow to invoke tools like SIRIUS or CSPP) and add a GUI to MZmine, which will invoke the algorithms.</p>

Jitsi Meet confines all conference content to a single browser window, leaving second monitors completely unused. Presenters cannot see the audience while screen sharing, moderators cannot watch the gallery while focusing on the active speaker, and educators cannot monitor student reactions while presenting. This project uses the Window Management API and React createPortal to open a coordinated secondary browser window on a different physical display while sharing the same Redux store and WebRTC connection. Each window can display an independent layout such as active speaker view or gallery view with no duplicate participants and zero extra bandwidth. The implementation includes smart screen detection via getScreenDetails, per tile video track management with stale frame prevention, a four tier active speaker priority chain using real time audio levels, responsive gallery grid with ResizeObserver, two tier style inheritance, and full window lifecycle management including conference leave cleanup. A working proof of concept with active speaker video, gallery view, layout switching toolbar, and speaking indicator borders is already integrated into the Jitsi codebase.

ScummVM includes a global fully configurable keymapper, but this requires engines to be adapted to use it. Hence the goal of this project is to integrate the customised ScummVM keymapper into the engine's input handling system. This involves modifying the engine-driven input handling code for mapping user input to in-game actions.

Renode.io is an open-source software simulator designed specifically for System on Chips (SoC) and Internet of Things (IoT) devices. It allows developers to simulate the behavior of their hardware and software designs before deploying them onto real devices, saving time and resources. Currently, there has been no documentation or testing mechanism on how to use the renode.io simulator for RTEMS. Thus, this project is created to take a look at which BSPs RTEMS have that are compatible to be used in the renode.io simulator, submit a patch to the RTEMS User’s Guide on how to use it on how to run the them on renode.io simulator, and possibly integrate the renode.io simulator into RTEMS testing ecosystem as an opt-in simulator solution.

Integrate automated 4-bit and 8-bit model weight quantization with fused FlashAttention-2 operators for efficient inference.

I believe Qubes is an easy and intuitive tool to achieve “reasonable” security, as it relies on explicit compartmentalization and force users to actively think about their actions. As massive cyberattacks are growing, Qubes is increasingly becoming an essential tool for the general public, reinforcing the need for UX- focused software. This project will make Qubes more accessible for people from diverse backgrounds by providing UX-focused GUI tools for software installation in templates.

<p>This project aims at firstly, investigating the performance of the current implementations against its alternatives at various levels of data transfer over the network connection for Duet, and further integrating the improvements into the PySyft stack.</p>

<p>The memory to CPU bottleneck is one of the fundamental and essential issues of commodity processors. With sweeply increasing computing speed, instructions might spend much of their time in waiting queues during read-store access. Nevertheless, there are also many available OS and microarchitecture designs for solving this performance complication. One of the important is the multi-level Translation Lookahead Buffer(TLB) Implementation. Based on the cache locality principle, it aids to keep the frequently used address translations near the core, hence amortizes the waiting time for instruction fetching and load-store units. With many levels in place, the less is the frequency of misses, the better is the performance. Thus, this proposal will aim to enhance the current TLB structure of the CVA6 (Ariane) core to a multi-level with L2 TLB on top of the existing L1 TLBs.</p> <p>Here, CVA6 is the application class and Linux bootable 64-bit RISC-V 1.7GHz CPU Core. It is also addable to the OpenPiton Heterogeneous Multicore Research Platform.</p>

Build the Policy Audit Point (PAP) for ACF-SDK that fires real attack payloads through the enforcement chain, records what gets caught and what slips through, and produces a coverage matrix. Includes 50+ attack patterns mapped to OWASP LLM Top 10, pytest integration, OpenTelemetry trace emission, and regression testing for policy changes. Structured as a research pre-registration targeting ACM AISec or IEEE S&P DLSP Workshop

<p>The goal of this project is to make matrixStats functions handle names in the same manner as the base R functions. The methods of handling names should not create an overhead that could have a significant negative impact on performance.</p>