Search Results for "computer-aided software engineering" - Page 24
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Showing 601 open source projects for "computer-aided software engineering"
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This is a MATLAB toolbox implementing Computer Vision and Pattern Recognition related algorithms. Check out http://cvprtoolbox.svn.sourceforge.net/svnroot/cvprtoolbox/. See also http://note.sonots.com/SciSoftware.html
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ViKi (Virtual Interactive keyboard Interface) is a global framework that enables contactless human machine interaction using computer vision techniques. Only a simple webcam is sufficient to emulate traditional devices such as mouse and keyboard do.
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AntHill is a Software Engineering project at the Warsaw University of Technology at the faculty of Computer Science. It simulates the behaviour of an anthill. Java technology
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A software to implement the existing stereo matching algorithms in computer vision, including the easiest SSD, and the newest algorithms.
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Cinefile
A category-based approach to exploring film data.
Cinefile is a prototype of a category-based method of database exploration. It allows the user to identify abstract categories of films by providing examples of category members, learns to classify films as belonging or not belonging to those categories, and provides a graphical interface for exploring and comparing categories. Cinefile is designed to work with data retrieved from the Internet Movie Database (imdb.com). This data is used for classification and is the subject of the... -
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Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.
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Laguna M.1
Flagship Poolside model for agentic coding and software engineering
...Laguna M.1 was designed to compete with leading frontier coding models on benchmarks such as SWE-Bench, Terminal-Bench, and other agentic engineering evaluations. It supports reasoning, tool calling, and long-context workflows, making it suitable for autonomous coding agents, software maintenance, debugging, and large-scale development projects. -
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Enjambre is a swarm simulation software. It consists of a generic method to describe objects and is extendable.
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JavaGO is an Open Source Java library for the Game of GO (weiqi, baduk) analysis. Implements: base game classes, montecarlo simulations, SGF reader/writer, game variants, GTP, etc. Elegant interfaces/class design. Speed efficient w/small footprint. TDD.
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A software package for evolving neural networks on several e-puck robots (www.e-puck.org, www.glowbots.com). The intention is to let the e-pucks evolve communication in cooperation with human beings.
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MiniMax-M2.7
Self-evolving AI model for agents, coding, and complex workflows
MiniMax-M2.7 is a large-scale open-weight language model designed for advanced agent-based workflows, professional software engineering, and complex productivity tasks. With 229B parameters, it introduces a self-evolution framework in which the model actively improves its own capabilities by updating memory, generating skills, and iterating through reinforcement learning experiments. This process enables it to autonomously refine systems, achieving measurable performance gains such as a 30% improvement in programming scaffolds. ... -
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qMaZda
Image analysis software
The open source project to port image analysis MaZda program to Linux and OS X platforms. See: http://www.eletel.p.lodz.pl/programy/mazda/ -
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Framework for modelling of Natural General Intelligence. This project aims at creation of open source AGI (Artificial General Intelligence) through modelling of natural thinking. See http://roland.pri.ee/bakalaureusetoo/ for theoretical details.
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eagle-i is an ontology-driven, RDF-based distributed platform for creating, storing and searching semantically rich data. eagle-i is built around semantic web technologies and adheres to linked open data principles.
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Devstral 2
Agentic 123B coding model optimized for large-scale engineering
Devstral 2 is a large-scale agentic language model purpose-built for software engineering tasks, excelling at codebase exploration, multi-file editing, and tool-driven automation. With 123B parameters and FP8 instruct tuning, it delivers strong instruction following for chat-based workflows, coding assistants, and autonomous developer agents. The model demonstrates outstanding performance on SWE-bench, validating its effectiveness in real-world engineering scenarios. ... -
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Supertagger
Software for assigning supertags.
Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree. -
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Devstral Small 2
Lightweight 24B agentic coding model with vision and long context
Devstral Small 2 is a compact agentic language model designed for software engineering workflows, excelling at tool usage, codebase exploration, and multi-file editing. With 24B parameters and FP8 instruct tuning, it delivers strong instruction following while remaining lightweight enough for local and on-device deployment. The model achieves competitive performance on SWE-bench, validating its effectiveness for real-world coding and automation tasks. -
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Laguna XS.2
Open agentic coding model optimized for local deployment
Laguna XS.2 is Poolside’s first open-weight Mixture-of-Experts model designed specifically for agentic coding and long-horizon software engineering tasks. The model contains 33B total parameters with only 3B activated per token, allowing it to deliver strong coding performance while remaining efficient enough to run locally on modern consumer hardware. It uses a hybrid attention architecture that combines Sliding Window Attention and global attention layers, reducing memory requirements and improving inference speed. ... -
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Qwable-v1
Agentic coding model combining Opus reasoning and Fable tools
...When configured as an agent, it can emit structured tool-use XML for file editing, shell commands, codebase navigation, and workflow automation. Qwable-v1 is designed specifically for software engineering, code editing, debugging, and autonomous coding workflows. -
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MiMo-V2.5-Pro
Flagship MoE model for long-context agents and complex coding
MiMo-V2.5-Pro is Xiaomi’s flagship Mixture-of-Experts (MoE) model built for the most demanding agentic, software engineering, and long-horizon reasoning tasks. It features approximately 1.02 trillion total parameters with 42B activated per inference, balancing extreme capability with efficient execution. The model supports a 1 million token context window, enabling it to maintain coherence across long workflows involving thousands of tool calls and multi-step reasoning chains. ... -
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Hy3 preview
Efficient MoE model for reasoning, coding, and AI agent workflows
Hy3 preview is Tencent Hunyuan’s latest open-weight Mixture-of-Experts language model, designed for advanced reasoning, coding, instruction following, and autonomous agent workflows. It is the first model built on Tencent’s rebuilt training infrastructure and introduces significant improvements in context learning, software engineering, and tool-based task execution. The model features 295B total parameters with only 21B activated during inference, plus a dedicated 3.8B Multi-Token Prediction (MTP) layer that accelerates generation through speculative decoding. Architecturally, it uses 192 routed experts with top-8 activation, a dense-MoE hybrid design, and a native 256K-token context window. ... -
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LongCat-2.0
Trillion-parameter MoE model for coding and million-token reasoning
LongCat-2.0 is Meituan’s flagship open-weight Mixture-of-Experts language model designed for frontier-scale coding, reasoning, and autonomous agent workflows. It features 1.6 trillion total parameters with approximately 48 billion activated per token, combining high capability with efficient sparse inference. The model was pretrained on more than 35 trillion tokens and trained entirely on a large-scale cluster of domestically developed AI accelerators, demonstrating stable frontier-scale... -
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Inkling-Small
Efficient multimodal MoE model for coding, tools, and reasoning
...Its 42-layer decoder routes each token through six of 256 specialized experts plus two shared experts, while hybrid local and global attention supports efficient processing. Inkling-Small performs strongly across software engineering, tool use, mathematics, vision, and audio benchmarks, including 80.2% on SWE-Bench Verified and 95.5% on AIME 2026. -
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Inkling
Frontier multimodal MoE model for coding and AI agent workflows
...Trained from scratch on approximately 45 trillion multimodal tokens, Inkling introduces controllable reasoning effort, allowing users to trade off latency and reasoning depth depending on the task. It is optimized for software engineering, tool use, and large-scale autonomous workflows, with strong performance on coding and agent benchmarks.