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docs/awesome/awesome-agi-cocosci.md

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* [Quantifying usability of domain-specific languages: An empirical study on software maintenance](https://www.sciencedirect.com/science/article/pii/S0164121214002799) - ***Journal of Systems and Software***, 2015. [[All Versions](https://scholar.google.com/scholar?cluster=3450893039446010260)]. A study to compare the usability of textual DSLs under the perspective of software maintenance, suggesting that the proposed metrics were useful: (1) to early identify DSL usability limitations, (2) to reveal specific DSL features favoring maintenance tasks, and (3) to successfully analyze eight critical DSL usability dimensions.
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* [Communicating Natural Programs to Humans and Machines](https://proceedings.neurips.cc/paper_files/paper/2022/hash/182aed0379591ebd1d655b2bdc152075-Abstract-Datasets_and_Benchmarks.html) - ***NeurIPS'22***, 2022. [[All Versions](https://scholar.google.com/scholar?cluster=13381039702346039142)]. While humans readily generate and interpret instructions in a general language, computer systems are shackled to a narrow domain-specific language that they can precisely execute. This makes building intelligent systems that can generalize to novel situations such as ARC difficult. Human-generated instructions are referred as `natural programs'. While they resemble computer programs, they are distinct in two ways: First, they contain a wide range of primitives; Second, they frequently leverage communicative strategies beyond directly executable codes.
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* [How Domain Experts Use an Embedded DSL](https://dl.acm.org/doi/abs/10.1145/3622851) - ***OOPSLA'23***, 2023. This work conducts a thematic analysis identified five key themes, including: the interaction between the eDSL and the host language has significant and sometimes unexpected impacts on eDSL user experience, and users preferentially engage with domain-specific communities and code templates rather than host language resources.
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* [The Child as Hacker](https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(20)30174-1) - ***Trends in Cognitive Sciences***, 2020. [[All Versions](https://scholar.google.com/scholar?cluster=13128656954836679743)]. The scope of human learning and development poses a radical challenge for cognitive science. The authors propose that developmental theories can address this challenge by adopting perspectives from computer science. Many of our best models treat learning as analogous to computer programming because symbolic programs provide the most compelling account of sophisticated mental representations. The authors specifically propose that children’s learning is analogous to a particular style of programming called hacking, making code better along many dimensions through an open-ended set of goals and activities. By contrast to existing theories, which depend primarily on local search and simple metrics, this view highlights the many features of good mental representations and the multiple complementary processes children use to create them.
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* [Communicating Natural Programs to Humans and Machines](https://proceedings.neurips.cc/paper_files/paper/2022/hash/182aed0379591ebd1d655b2bdc152075-Abstract-Datasets_and_Benchmarks.html) - ***NeurIPS'22***, 2022. [[All Versions](https://scholar.google.com/scholar?cluster=13381039702346039142)]. While humans readily generate and interpret instructions in a general language, computer systems are shackled to a narrow domain-specific language that they can precisely execute. This makes building intelligent systems that can generalize to novel situations such as ARC difficult. Human-generated instructions are referred as “natural programs”. While they resemble computer programs, they are distinct in two ways: First, they contain a wide range of primitives; Second, they frequently leverage communicative strategies beyond directly executable codes.
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* [Symbolic metaprogram search improves learning efficiency and explains rule learning in humans](https://www.nature.com/articles/s41467-024-50966-x) - ***Nature Communications***, 2024. [[All Versions](https://scholar.google.com/scholar?cluster=7670274141609367282)]. Symbolic models based on program learning successfully explain rule-learning in many domains, but performance degrades quickly as program complexity increases. It remains unclear how to scale symbolic rule-learning methods to model human performance in challenging domains. This work shows that symbolic search over the space of metaprograms—programs that revise programs—dramatically improves learning efficiency. On a behavioral benchmark of 100 algorithmically rich rules, this approach fits human learning more accurately than alternative models while also using orders of magnitude less search. The computation required to match median human performance is consistent with conservative estimates of human thinking time. The results suggest that metaprogram-like representations may help human learners to efficiently acquire rules.
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### Problem Solving

docs/awesome/awesome-angular.md

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* [angular-techs-logos](https://github.com/criar-art/angular-techs-logos) - Library of tech related icons.
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* [ngx-x-browser-svg-mask](https://github.com/bmartinson/ngx-x-browser-svg-mask) - Directive to easily achieve cross browser compliance while creating SVG masks.
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* [boringer-avatars](https://github.com/cmgriffing/boringer-avatars) - A fork from [boring-avatars](https://github.com/boringdesigners/boring-avatars). This rewrites the base as Mitosis components and exports into multiple framework flavors including [Angular](https://github.com/cmgriffing/boringer-avatars/tree/main/packages/lib-angular).
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* [@semantic-icons/heroicons](https://www.npmjs.com/package/@semantic-icons/heroicons) - [Semantic icons](https://github.com/khalilou88/semantic-icons) helps developers to use [Heroicons](https://heroicons.com/) icons inside Angular projects.
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#### Images
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* [store-service](https://github.com/ngxp/store-service) - Adds an abstraction layer / facade between Angular components and the NgRx store.
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* [ngrx-entity-relationship](https://github.com/satanTime/ngrx-entity-relationship) - ORM selectors for Redux, `@ngrx/store`, `@ngrx/entity`, and `@ngrx/data`. Ease of relationships with entities.
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* [ngx-signal-store-query](https://github.com/k3nsei/ngx-signal-store-query) - Signal Store feature that bridges with [Angular Query](https://tanstack.com/query/latest/docs/framework/angular/overview).
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* [SmartNgRX](https://github.com/DaveMBush/SmartNgRX) - A library that hides most of NgRx from the developer for CRUD operations while still using NgRx under the hood and allowing you to use it with existing NgRx code.
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#### RxJS
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docs/awesome/awesome-cpp.md

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* [nanopb](https://github.com/nanopb/nanopb) - Small code-size Protocol Buffers implementation in ANSI C. [Zlib]
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* [protobuf](https://github.com/protocolbuffers/protobuf) - Protocol Buffers - Google's data interchange format. [BSD]
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* [protobuf-c](https://github.com/protobuf-c/protobuf-c) - Protocol Buffers implementation in C. [BSD]
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* [Protocol Puffers](https://github.com/PragmaTwice/protopuf) - A little, highly templated, and protobuf-compatible serialization/deserialization header-only library written in C++20. [Apache-2.0]
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* [SimpleBinaryEncoding](https://github.com/real-logic/simple-binary-encoding) - encoding and decoding application messages in binary format for low-latency applications. [Apache2]
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* [upb](https://github.com/protocolbuffers/upb) - A small protobuf implementation in C. [BSD]
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* [Wirehair](https://github.com/catid/wirehair) - O(N) Fountain Code for Large Data. [BSD-3-Clause]

docs/awesome/awesome-go.md

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- [parallel-fn](https://github.com/rafaeljesus/parallel-fn) - Run functions in parallel.
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- [pond](https://github.com/alitto/pond) - Minimalistic and High-performance goroutine worker pool written in Go.
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- [pool](https://github.com/go-playground/pool) - Limited consumer goroutine or unlimited goroutine pool for easier goroutine handling and cancellation.
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- [rill](https://github.com/destel/rill) - Go concurrency with channel transformations. No boilerplate, type safety, batching and error handling.
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- [rill](https://github.com/destel/rill) - Go toolkit for clean, composable, channel-based concurrency.
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- [routine](https://github.com/timandy/routine) - `routine` is a `ThreadLocal` for go library. It encapsulates and provides some easy-to-use, non-competitive, high-performance `goroutine` context access interfaces, which can help you access coroutine context information more gracefully.
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- [routine](https://github.com/x-mod/routine) - go routine control with context, support: Main, Go, Pool and some useful Executors.
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- [semaphore](https://github.com/kamilsk/semaphore) - Semaphore pattern implementation with timeout of lock/unlock operations based on channel and context.
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- [algernon](https://github.com/xyproto/algernon) - HTTP/2 web server with built-in support for Lua, Markdown, GCSS and Amber.
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- [Caddy](https://github.com/caddyserver/caddy) - Caddy is an alternative, HTTP/2 web server that's easy to configure and use.
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- [Clace](https://github.com/claceio/clace) - Clace makes internal tool deployment and management easy by implementing an app server for containerized webapps.
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- [consul](https://www.consul.io/) - Consul is a tool for service discovery, monitoring and configuration.
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- [cortex-tenant](https://github.com/blind-oracle/cortex-tenant) - Prometheus remote write proxy that adds add Cortex tenant ID header based on metric labels.
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- [devd](https://github.com/cortesi/devd) - Local webserver for developers.
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- [discovery](https://github.com/Bilibili/discovery) - A registry for resilient mid-tier load balancing and failover.
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- [dudeldu](https://github.com/krotik/dudeldu) - A simple SHOUTcast server.
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- [dummy](https://github.com/neotoolkit/dummy) - Run mock server based off an API contract with one command.
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- [Easegress](https://github.com/megaease/easegress) - A cloud native high availability/performance traffic orchestration system with observability and extensibility.
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- [Engity's Bifröst](https://bifroest.engity.org/) - Highly customizable SSH server with several ways to authorize a user how to execute its session (local or in containers).
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- [etcd](https://github.com/etcd-io/etcd) - Highly-available key value store for shared configuration and service discovery.
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- [Euterpe](https://github.com/ironsmile/euterpe) - Self-hosted music streaming server with built-in web UI and REST API.
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- [Fider](https://github.com/getfider/fider) - Fider is an open platform to collect and organize customer feedback.

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