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<p>RISC-V is an open ISA freely available for all types of use. The RISC-V ISA has been designed with small, fast, and low-power real-world implementations in mind, but without "over-architecting" for a particular microarchitecture style.</p> <p>The RISC-V being a base ISA is carefully restricted to a minimal set of instructions sufficient to provide a reasonable target for compilers, assemblers, linkers, and operating systems (with additional supervisor level operations), and so provides a convenient ISA and software toolchain skeleton around which more customized processor ISAs can be built. This project thus aims to leverage and demonstrate the advantages of myHDL and python in general in the field of CPU design by implementing a RISC-V CPU (in myHDL) and other CPU design utilities. Since RISC-V is a base ISA, having a myHDL based implementation becomes a essential and would enable a lot of Computer Architecture researchers to design and test RISC-V based derivatives using myHDL and python based utilities.</p>

This proposal aims to develop an information theoretic approach to filter out artificial information from real information in geospatial datasets. The project will use the bitinformation framework to distinguish between real and false information, where real information is defined as the mutual information between adjacent bits. The proposed algorithm will filter out artificial information, which is a consequence of prior compression, from real information, which reflects the underlying signal. The project will involve a theoretical review, test case generation, algorithm development, evaluation, and integration into xbitinfo, a software package that implements the bitinformation framework. The resulting artificial information filter will provide a valuable tool for users who may not have access to high-precision/uncompressed data, and it will enhance the accuracy and reliability of geospatial data analysis. As a participant in the Google Summer of Code, I am excited about the opportunity to work on this project and contribute to the development of an open-source software tool that will benefit the scientific community.

<p>Enable full application of Time-Frequency Analysis tools on Source Estimate M/EEG neurophysiological data by integrating <code>mne.SourceEstimate</code> objects with <code>mne.time_frequency.tfr</code> functions.</p>

<p>Command line is the most flexible and powerful platform. It is also the fastest way to work compared to a GUI. Also, the command line will give scope for automation and scripting. Currently, the command line handler framework in Pharo is used. Pharo comes with many built-in handlers. ​ There is also Scale​ repository which is also used to write scripts. Due to the increased use of scale, the complexities in Pharo has been raised to a higher level leading to core problems in Pharo. I wish to solve these problems, thereby improving the command line management.</p>

Increase in amount of recording sensors in EEG, MEG and iEEG has brought about a need in new approaches for analysis of the data. Such approaches include source separation and decoding. This project is aimed at (1) implementing a supervised source separation technique called generalised eigendecomposition (GED) with accompanying visualisations, (2) refactoring, modernising and enhancing the implementation of decoding classes already implemented in MNE-Python.

Pwndbg has supported LLDB internally since 2024, and in general availability as of the 2025.01.20 release. That support is, however, still in its infancy. Currently, all the test code in Pwndbg is still strongly tied to GDB, meaning that, aside from manual checks, there is nothing keeping changes to the codebase from silently breaking the LLDB subsystem. And, while there is support for attaching to and debugging programs running on platforms other than Linux, there are not as many features catering to the specifics of those platforms as there are for traditional Linux distributions. In particular, the process by which mobile debugging is done is still poorly documented, intricate, and not thoroughly tested. These shortcomings hold back LLDB Pwndbg from being as useful to its users as it can be.

<p>The main objective of this project is to create such interfaces (by the means of various visualizations of the library) that makes it easier for user to:</p> <ul> <li>Access the required filter curves</li> <li>Calculate the photometry of a star's spectrum under a certain filter set</li> </ul> <p>To achieve this, I propose to develop several adequate visualizations by enabling interactivity and UI controls, such that they serve as <strong>analytical web interfaces</strong> through which user can access what they need in a couple of clicks! These interfaces will be made accessible to the user by integrating them within living Sphinx docs, such that they will be auto generated when building the docs.</p> <p>Besides, I also aim to well document the wsynphot package after integrating the developed interfaces in it, ultimately reshaping the entire package. Hence, user can <em>auto-generate both the filter curves &amp; photometry</em> directly from the docs as per their requirements, by using these responsive interfaces.</p>

PyAfipWs is a vibrant community building unique interfaces, tools, and apps for Argentina's gov't. web services (soap, com/dll simil-ocx, pdf, dbf, xml, json, etc.). Currently, they have support using GitHub actions to automatically build installations when a pull request gets merged with the main branch. But it needs improvements in building a one-click NSIS(Nullsoft Scriptable Install System) Installer when a pull request merges. In addition, I’ll work on improving the unit test coverage and packaging of the module to PyPi. And lastly, If I manage my time well, I’ll happily provide a web service for testing.

<p>In the above proposal we are showing the idea of implementing JPEG Encoder(backend) in python using existing MyHDL Library. A working module and its corresponding testbench is desired.</p>

<p>Panda3D is an open source framework for 3D rendering and games. It combines the speed of C++ with the ease of use of Python in order to provide users a fast rate of development without sacrificing on performance. The project I wish to work upon is Integration of Navigation-mesh Toolset for Games in Panda3D. Recast and Detour are tools/libraries for building navigation meshes and performing pathfinding. Once these tools/libraries are successfully integrated with Panda3D, it would be possible for a Panda3D actor to move from the source to the destination avoiding collisions with the walls and inappropriate paths.</p>

Generics are a common functionality found in statically typed programming languages, allowing easier maintenance of programs which differ only in their types. However, generics are not yet supported in the statically-typed LPython. Generics in LPython can be implemented similar to the approach taken by C++ templates. We can regard generic functions as functions with type parameters, whose parameters are made concrete and checked by function calls on AST level. The end result of the project would be generic function support for LPython with option for specialization, along with sufficient integration tests and documentations.

As highlighted during the 2025 Blender Conference, one of the primary challenges facing the Compositor is managing complexity. To address this, the goal of this proposal is to make it as accessible as possible by porting over familiar nodes from Geometry Nodes. This project aims to: - Develop a future-proof classification between the two modules. - Port matrix & math utility nodes into the Compositor: Matrix SVD, Bit Math, Boolean Math, Integer Math, Compare, Float To Int, Hash Value, and Random Value. - Extend GPUType to include boolean, integer and integer vector types. - Ensure UI and behavior consistency between ported nodes and existing ones, including full support for the GPU Compositor. - Implement regression testing for all newly ported nodes. - Document the rationale behind node selection, implementation and functionality in the new context.

Blender’s edit-mode smooth operator is a simple iterative uniform Laplacian average. While functional for light cleanup, it has four fundamental limitations that become severe in production workflows: - Volume shrinkage — The operator is a diffusion process that inherently contracts the mesh. A UV Sphere loses 91.3% of its volume after 100 iterations. - No frequency selectivity — The operator cannot distinguish noise from shape. For mild noise (σ≤0.01), smoothing any number of iterations makes the mesh less faithful to the clean original. For moderate noise (σ=0.02), there is a narrow useful window (~5 iterations) before shape degradation dominates. - Selection boundary artifacts — Smoothing a partial selection produces a sharp displacement discontinuity at the boundary (measured gradient: 0.067, 4× the interior average), creating a visible crease ring. This project will implement three capabilities for edit-mode: volume-preserving smooth, frequency-aware smooth, and geometry pinning with boundary falloff blending.

The aim of this project is to extend LPython's OOP capabilities to enable the porting of CPython modules. The proposal is divided into three main parts: improving the utility of classes in LPython using general imports and dunder methods, porting CPython's re and json modules and addressing some miscellaneous goals like adding advanced data structures and improving string attributes.

Borg Collective is a well-known organization that offers a range of Python-based backup tools, including Borg, Borgmatic, and Vorta. Borg is a file backup tool that performs tasks like compression, encryption, authentication, and data deduplication. Vorta is a desktop GUI for Borg, and Borgmatic is a CLI wrapper around it. With this project, I aim to improve Vorta by adding some essential features that users have frequently requested, enhancing its user experience, making it easier for beginners to use, and designing and developing new interfaces. As for Borgmatic, I aim to expand its already powerful capabilities, particularly in the areas of database backups and restores. I also want to help decrease the number of unresolved issues in the Borgmatic repository and work closely with project maintainers and users to incorporate more features into the project.

The function of the list configuration tool is to export the list and configuration of the administrator and generate a JSON file to store them. At the same time, you can also use these JSON files to import the list and configuration in the file into other users. This is a process of converting the server's online data into files for storage, backup and data migration.

<p>EOS-icons deliver a set of icons in an iconic font and also provides a few animated icons. For developers working on products like plugins or executable files, it is more efficient to be able to get a .PNG or .SVG of the icon in any color or size. This project aims to solve this problem by creating a Icon Customization tool that enables user to download icons in any color and size. It also aims to add more animated icons to the current set.</p>

<p>Testing is a nice-to-have tool/utility for developers to check for breaks in early stages of development cycle which is less expensive. Automated testing makes the whole process less time time consuming. The goal of this project is to:</p> <ul> <li>Extend the framework and write tests for Physics modifiers, Curve types and remaining Deform and Generate modifiers.</li> <li>Generalization and refactoring of the framework to have non-duplicated code and classes.</li> <li>Working on a test object generation script to "fully" automate the testing procedure as there will be no need for interaction with the UI(Blender).</li> </ul>

<ul> <li>Improving Guillotina API by making it more compliant to JSON-LD.</li> <li>Implementing WebSocket endpoint for all the API functionalities </li> <li>JSON validation for all the payloads by well-defined JSON schemas.</li> <li>Updating swagger documentation.</li> <li>Versioning of API by adding a version number to the endpoint URLs.</li> <li>And writing kubernetes configurations along with helm charts for Guillotina.</li> </ul>

LPython currently doesn't support classes and object oriented programming paradigm. This goal of this project is to implement classes and OOP features like inheritance and polymorphism in LPython at the ASR and LLVM level. This will enable porting of standard library modules in Python to LPython. The project involves adding class semantics to the Abstract Semantic Representation (ASR) in LPython, allowing for the inclusion of member functions with local scope and enabling seamless integration of object-oriented programming (OOP) features. This entails modifications to the ASR nodes, the AST-to-ASR conversion process, and the ASR-to-LLVM translation to facilitate function calling and method invocation. Additionally, the project includes extending operator functionality, transitioning from dataclass to struct decorators, implementing limited dunder functions, and thorough integration testing.

This project in Lpython and LPython is a Python compiler. It is in heavy development, currently in pre-alpha stage. Some of the goals of LPython, my project will add three features in compiler.

This project introduces a library of 7 data structures to the Pharo ecosystem, replacing O(N) bottlenecks with resilient, mathematically proven structures (including B Trees, K-D Trees, and Persistent Arrays). Following a full design approach, the implementations will be stress-tested using Competitive Programming datasets to guarantee architectural integrity under heavy load. Finally, the project utilizes VM-level tools (TimeProfiler and MemoryProfiler) to empirically benchmark performance, delivering production-ready infrastructure alongside interactive visual inspectors.

Blender's UI regression test suite leaves most of the editor surface untested in CI, meaning regressions are caught only by manual review. This project extends the existing UI simulate testing framework with new targeted tests covering Window Manager state transitions, all practical editor/region types, menu and operator search per editor, tool/modifier/preference draw stability, and interaction-heavy flows like drag/drop, pie menus, and selection behavior. All tests integrate into the existing CI, with documentation covering how to run and extend UI regression tests within the framework.