Submission declined on 13 April 2026 by Pythoncoder (talk). This draft appears to contain text generated by a large language model (such as ChatGPT). You cannot use LLMs to generate article content. LLM-generated pages with certain obvious signs of being machine generated may be deleted without notice. These tools are prone to specific issues that violate our policies: hallucinations: they often invent false information and cite non-existent references. unencyclopedic tone: they tend to be vague, promotional, or essay-like, rather than neutral and factual. copyright issues: they may closely paraphrase existing text, leading to copyright violations. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. See the advice page on large language models for more information. If you would like to continue working on the submission, click on the "Edit" tab at the top of the window. If you have not resolved the issues listed above, your draft will be declined again and potentially deleted. If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors. Please do not remove reviewer comments or this notice until the submission is accepted. Where to get help If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews. If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed. How to improve a draft Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia. Help:Wikitext – how to use the markup Help:Referencing for beginners – how to include references Wikipedia:Article development – how to develop your article Wikipedia:Writing better articles – how to improve your article Wikipedia:Verifiability – make sure your article includes reliable third-party sources You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Add tags to your draft Editor resources Easy tools: Citation bot (help) | Advanced: Fix bare URLs Declined by Pythoncoder 56 days ago. Last edited by Jerryobject 47 days ago. Reviewer: Inform author. Resubmit Please note that if the issues are not fixed, the draft will be declined again.

Koin is an dependency injection framework for the programming language Kotlin. It is designed for use in Android, Kotlin Multiplatform, and backend applications built with Ktor. It is free and open-source software with an Apache License 2.0.

Koin was created by Arnaud Giuliani in 2017 and is maintained by Kotzilla and open-source contributors.^[1] Unlike annotation-based frameworks such as Dagger or Hilt, Koin uses a domain-specific language (DSL) written in pure Kotlin to declare and resolve dependencies at runtime. It does not rely on code generation or reflective programming (reflection).^[2]

• Kotlin DSL – Dependencies are declared using a module DSL, making configuration concise and readable.
• No code generation – Dependencies are resolved at runtime, resulting in faster build times compared to annotation-processing frameworks.
• Multiplatform support – Koin supports Kotlin Multiplatform projects, enabling shared dependency injection across Android, iOS, desktop computer, and backend targets.
• Android integration – Provides built-in support for Android ViewModel, Jetpack Compose, and lifecycle-aware scopes.
• Ktor integration – Provides first-class support for Ktor server applications.
• Annotations module – An optional annotations-based API (koin-annotations) provides compile-time safety for teams migrating from Dagger or Hilt.^[3]

Koin was first released in 2017 by Arnaud Giuliani, a Google Developer Expert for Kotlin and cofounder of Kotzilla.^[4] Since 2018, it has been one of the most widely adopted Kotlin frameworks.^[1] Koin 4.0, released in 2024, introduced support for Kotlin 2.0 and expanded Compose Multiplatform integration.^[5]

The project is hosted on GitHub under the InsertKoinIO organization.

In the Android and Kotlin ecosystem, Koin is commonly compared to:

• Hilt – developed by Google, uses annotation processing and code generation; provides deeper integration with Android lifecycle components but increases build times.
• Dagger – a compile-time DI framework for Java and Kotlin, known for strict type safety but a steeper learning curve.
• Kotlin-inject – a newer compile-time DI library for Kotlin Multiplatform, with a smaller community than Koin.^[6]

• Dependency injection
• JetBrains
• List of Kotlin software and tools

• Official website
• koin on GitHub