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This project will build a portable Kafka Streams runner for Apache Beam so that Beam pipelines can run on Kafka Streams using the Beam Fn API. The runner will translate portable Beam pipeline protos into Kafka Streams topologies and support a working skeleton for core transforms: Read, stateless ParDo, GroupByKey, Combine, non-merging windowing, and Flatten. The implementation will focus on correct watermark propagation, commit-based bundle boundaries, exactly-once semantics, and integration with the existing Beam portability stack. Deliverables include a new runners/kafka-streams module, runner entry points, a pipeline translator with transform-specific translators, watermark and bundle management, tests using TopologyTestDriver and real Kafka-based integration coverage, and documentation for the Beam community.

<p>This proposal aims to add call hierarchy support in Haskell Language Server(HLS).</p> <p>Language Server Protocol(LSP) has <a href="https://microsoft.github.io/language-server-protocol/specifications/specification-current/#textDocument_prepareCallHierarchy" target="_blank">supported</a> call hierarchy in 3.16, which make us implement it in HLS possible.</p> <p>Inspired by <a href="https://github.com/haskell/haskell-language-server/issues/738" target="_blank">this issue</a>, my proposal involves the following steps this summer to contribute to call hierarchy:</p> <ol> <li><a href="https://github.com/haskell/lsp" target="_blank">LSP</a> spec support.</li> <li><code>prepareCallhierarchy</code> implementation.</li> <li><code>incomingCalls</code> implementation.</li> <li><code>outgoingCalls</code> implementation.</li> <li>Test</li> </ol> <p>I hope I can contribute to HLS to go further this summer.</p>

<p>This project's goal is to offer the Nautilus' community an easy way to test their contributions with consistent results and a profiling/coverity aspect in order to easily identify possible issues. The project itself includes the addition of unit tests, integration tests, coverity and profiling tools as well as a rework on the NAUTILUS_DEBUG framework.</p>

Dagger.jl currently serializes all GPU tasks onto a single stream per device, leaving independent DAG branches unable to run concurrently and GPU hardware severely underutilized. This project implements multi-stream execution for the CUDA and ROCm backends by replacing the single fixed stream with a per-device stream pool, integrating stream-aware scheduling into the task dispatch layer, and replacing the global device barrier with event-based synchronization. The expected outcome is a significant reduction in end-to-end latency, improved Streaming Multiprocessor occupancy, and meaningful overlap between memory transfers and kernel execution.

Optimize the React Native bridge and new architecture to improve startup times and animation framerates on lower-end Android devices. (MLH Fellowship)

<p>A new component of App Inventor for users to display charts on Android device. I discussed the general idea as well as some details of implementation in this proposal.</p>

<p>Over the years, Mozilla has shifted to using Taskcluster as its primary continuous integration system. Communication becomes essential between the various components when scaling the infrastructure. Mozilla uses Pulse to enable an exchange of information Mozilla’s systems. Pulse is actually a RabbitMQ server which uses AMQP ( and follows a Publish--Subscribe pattern). Taskcluster-events is a service that allows web clients to listen for pulse messages without RabbitMQ credentials and without the need for a TCP connection to the RabbitMQ server. However, currently, taskcluster-events is old and poorly designed, without protocol specification. This proposal aims to completely rebuild taskcluster-events from scratch, ensuring it is robust and free of major bugs / failures.</p>

<p>In distributed TensorFlow, identifying the nodes without domain name collision is a big challenge. CoreDNS supports DNS Name Server Identifier (NSID) which allow a DNS server to identify itself. So we can deploy CoreDNS for every node in the distributed TensorFlow cluster to solve this problem. There are two ways to achieve this goal. One way is to set up a distributed Key-Value store like zookeeper or etcd, and another way is to assign each node with an order based on the timestamp. My GSoc work aims to implement one of the approaches above.</p>

This proposal outlines a plan to extend the cBioPortal MCP server with interactive genomic visualisation applications via MCP Apps that allow AI assistants like Claude and ChatGPT to render rich, interactive UI components directly within conversations. Rather than returning raw text or static data, the MCP server will serve four self-contained visualization apps (OncoPrint, Survival Analysis, Mutation Mapper, and Study Summary) as embeddable iframes, using bidirectional JSON-RPC communication via postMessage. This transforms the way researchers interact with cancer genomics data through AI, making cBioPortal the first genomics platform to offer interactive visual exploration inside AI chat interfaces.

<p>WormBase is a comprehensive research knowledge base on the genetics, genomics and biology of C. elegans and related nematodes. Biologists access these vast information through a web port which often provides information in many tables. However, these tables where developed years ago based on HTML and jQuery, with certain features depending on Flash. Their limitations and usability issues are more pronounced now.</p> <p>In this project, I will rebuild more functional and performant table using React. New implementation of table will be a generic and customizable React component, and it will serve WormBase data with the ability to search, filter, sort, paginate, and export all or parts of the table. Furthermore, the new implementation provides not only better data visibility, but also a better user experience by significantly reducing the existing load times.</p>

webpack-dev-server is a development tool in the webpack group projects. It eases the development of javascript projects by providing an instant development server for bundling of javascript projects. it leverages webpack-dev-middleware under the hood and provides fast, in-memory access to the assets. The project has several tests using puppetter as test runner, currently the puppeteer tests, end to end tests are flaky and there is a need to refactor them to be more stable and robust.This proposal is aimed at introducing Playwright to replace Puppeteer. By replacing the test runner framework, the contributor also proposes to refactor end to end tests by reducing duplication in them.

<p>To revamp current eventyay site into new one from Emberjs to React with NEXT and setup frontend modelling ,similar UI-UX behaviour, write tests and maintain quality code.</p>

Description: Cluster API Provider GCP (CAPG) enables the creation of Kubernetes clusters in GCP with Cluster API. With increasing adoption of Cluster API (CAPI) in general and of CAPG we want to improve the supportability of CAPG, especially for production environments. The first part of this is to add telemetry/tracing using OpenTelemetry so that we can understand and visualize the flow of reconciliation within the provider. The next part is to add a **pprof** endpoint that can be optionally enabled to enable operations/support users to collect profiling information from a running instances of CAPG. Expected Outcome: This work will enable tracing and profiling of a running instance of CAPG (along with supporting docs) to supports operations/support engineers.

<p>The main goal of my project is implementing an HTTP/WebSocket server running inside the game server process that will allow access to Terasology functionalities for players and server admins (for example kicking players, teleporting, changing game properties, adjusting game time, etc - according to user permissions) through those protocols, and appropriate user-friendly clients to interact with the service.</p>

<p>ListenBrainz currently only displays the list of listens imported into a user's profile and the basic stats about the artists that a user has listened to. There isn't much a user can do with the recordings/listens imported into their profile. Love, hate and delete are the basic features that can be provided to the users. Love/hate feature will help in perceiving the user's taste in music and hence refine the recommendations that are generated for them. Keeping in mind the decision to migrate to Timescale DB and upon a discussion on IRC <a href=""https://chatlogs.metabrainz.org/brainzbot/metabrainz/2020-03-16/?msg=4550029&amp;page=1"" target="_blank">here</a> it was decided to club the delete a listen feature into the love/hate a recording project. My proposal for this project aims to</p> <ul> <li>Add the 'love/hate a recording' feature</li> <li>Add the 'delete a listen' feature</li> <li>Adding the UI components for the above features and revamping the 'My Listens' page.</li> </ul>

OpenSSL 3.2 introduced native QUIC support, enabling HTTP/3 on top of the world’s most widely deployed TLS library. Apache httpd, however, is still architected around TCP-based connections and its Multi-Processing Modules (MPMs), which makes integrating QUIC and HTTP/3 non-trivial. An example codebase (openssl-h3-examples) already demonstrates HTTP/3 using OpenSSL’s QUIC support and nghttp3 in a standalone server, and reuses patterns inspired by mod_http2, but it remains experimental and is not integrated into httpd as a module. This project proposes a new HTTP/3 module for Apache httpd, building on OpenSSL QUIC and nghttp3, and aims to resolve the architectural mismatch between httpd’s TCP-oriented worker model and QUIC’s UDP-based, stream-multiplexed transport. The goal is a maintainable, reviewable prototype module that the Apache HTTP Server community can evaluate and evolve toward production readiness.

<p>FOSSology frontend is built using the Symfony framework of PHP. It needs to get revamped to make it faster for development, more adaptive to newer technologies, and impart a modernized look. I would rewrite the UI in React from scratch while ensuring a <strong>highly scalable</strong>, <strong>flexible</strong>, and <strong>easy to use and maintain</strong> code architecture. Also, I will be upgrading the existing API and would integrate it with the new frontend code.</p> <p><strong>Deliverables</strong> of this project:</p> <ul> <li>A fresh modern look to the FOSSology UI</li> <li>Complete migration of frontend to React</li> <li>Upgradation of API to provide more functionalities</li> <li>Documentation of frontend code</li> </ul>

This project extends the OpenAFS fs examine command to provide visibility into each component of a given path, instead of only the final object. In a distributed file system, paths may traverse multiple volumes, cells and mount points, making it difficult to understand how a path is resolved. The proposed solution introduces a new optional flag that iteratively resolves each component of a path and retrieves volume and file information using existing pioctl calls. The implementation will handle intermediate path construction, mount point detection, symbolic links and error cases while preserving backward compatibility. The final deliverables include a working implementation of the new flag, support for edge cases such as mount points and symlinks, updated documentation and tests to validate correctness.

This project aims to enhance Sysprof by integrating eBPF-based profiling to reduce overhead and improve performance. Currently, Sysprof relies on accessing numerous /proc files, which involves frequent syscalls, file descriptor operations, and context switches, creating performance bottlenecks. By utilizing eBPF, data collection can be done directly within the kernel, eliminating the need for constant /proc access and minimizing context switches. This approach not only lowers overhead but also ensures consistent and atomic data capture. eBPF also allows for advanced features such as system-wide syscall monitoring and process creation tracking, which were difficult to implement previously. By adopting eBPF, Sysprof becomes more efficient, scalable, and feature-rich, laying the foundation for future enhancements and transforming it into a modern, versatile profiling tool.

<ul> <li>API to insert/update/delete data on server. </li> <li>Redesign/enhance web UI </li> <li>Authenticated review/rating system </li> <li>Reduce data redundancy</li> <li>Speaker login</li> <li>Improve exporting to ical</li> </ul>

Haskell language server (HLS) implements the server part of Language Server Protocol (LSP) to improve user experience of reading and writing Haskell. Signature help is a LSP language feature which shows function signatures and documentation when the cursor is inside a function application. It can also highlight part of the signature related to the current parameter the cursor is at. Users want this useful feature. This project implements signature help for HLS.

<p>An open source software project should allow everyone to participate. Inherently this can cause the project to grow over the boundaries of its initial scope rapidly. In Pocket Code this has caused the components to grow into each other, which in turn has made it difficult to maintain a stable and adaptable architecture. I would like to rewrite the existing code into a clearly structured and clearly separated architecture with focus on the distinction between UI representation and functionality.</p>

In this project, we aim to build a Rust-based log processing framework. Applications built on this framework will be compiled into WebAssembly and run in WasmEdge containers side by side with Linux containers and apps. The WasmEdge app collects logs from other containerized apps and then sends them to a streaming database or processing pipeline. - Expected outcome: * Create a Rust framework with 3 traits similar to the [`Transformer`](https://github.com/second-state/MEGA/blob/main/mega_etl/src/lib.rs#L99) trait in the [MEGA framework](https://github.com/second-state/MEGA). * The `Collector` trait abstracts operations needed for a log collector. * The `Transformer` trait abstracts the transformation algorithms that can be applied to the logs. * The `Destination` trait abstracts operations needed to send transformed to a streaming data pipeline or database. * Implement at least two `Collector`s. One for MySQL database binlog and the other for a generic log file in a Linux container in the same Kubernetes pod. * Implement at least two `Transformer` algorithms supported by [FileBeat](https://www.elastic.co/guide/en/beats/filebeat/current/filebeat-overview.html). * Implement at least three `Destination`s. One for a Kafka queue, one for a Redis database, and the other for ElasticSearch. * Provide CI and demo test cases. * Provide documentation and tutorials.