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Trivial examples are not enough, as they often do not reflect real world conditions. 8. . functions and destructuring component methods (though this language feature is only useful to Kotlin consumers). Namely, support for generating Dagger factories (example) and Moshi Kotlin models (based on this pull request). It takes a Java developer just a few hours to learn Kotlin. We believe that the excessive use of this feature, the non-share of their classloader, and poorly written checkers might be the cause of this overhead. Structs/exceptions/unions are generated as standard value types (POJOs). Artificial Intelligence / Machine Learning, Measuring Kotlin Build Performance at Uber, Improving Uber’s Mapping Accuracy with CatchME, Introducing the Uber Research Publications Site, Meet Michelangelo: Uber’s Machine Learning Platform, Introducing Domain-Oriented Microservice Architecture, Uber’s Big Data Platform: 100+ Petabytes with Minute Latency, Why Uber Engineering Switched from Postgres to MySQL, H3: Uber’s Hexagonal Hierarchical Spatial Index, Introducing Ludwig, a Code-Free Deep Learning Toolbox, The Uber Engineering Tech Stack, Part I: The Foundation, Introducing AresDB: Uber’s GPU-Powered Open Source, Real-time Analytics Engine. Although we have a metric that tells us the percentage of Java files present in the project, it is tightly coupled to the size of the project; in other words, as the percentage of Java changes, so does the size of the project. Figure 8: We measured project performance between Pure Kotlin with Kapt (pink) and pure Kotlin (blue) setups, on the left, and pure Java with Apt (brown) and pure Java (turquoise), on the right. Kotlin JS gets the new Kotlin JS IR compiler, which is still in alpha today. What’s more, the striking resemblance of the two languages can help in native development of one app for both Android and iOS. Kotlin has many compelling advantages. Buck support for Kotlin was added by the open source community and it is not being actively maintained. In addition, the experiment execution was too slow (on average, the experiment takes two hours to finish on CI hardware). We hope that this analysis can serve as a north star for other organizations  who leverage Kotlin. We wanted our analysis to be build system agnostic and keep the focus as close to kotlinc vs. javac as possible. But the ‘Kotlin vs Java performance’ debate is ongoing. «I believe the future is bright for Ktor! These are pure JVM projects. This is exciting for mobile app development as maintaining an app across Android and iOS can become more intuitive. 4. Although we expected (or at least hoped) that there was a linear correlation between compilation time and number of files, this was a great indicator that we did not need to worry too much about creating enforcements around module size. Enjoy the benefits of a rich ecosystem with a wide range of community libraries. Since we cannot infer that the work performed by each thread throughout a build execution is deterministic, we do not want multi-thread mode to interfere with the times from the compiler thread. The most interesting insights are described below: is currently adding an overhead of ~70 percent on top of pure Java (baseline), Error Prone, a static analysis tool for Java. Kotlin with Kapt adds a ~95 percent overhead when compared with pure Kotlin only. It’s developed by JetBrains who are currently working to bring Kotlin to embedded systems and iOS as well, potentially making it a one-stop language for all application areas. However, with over 20 Android applications and more than 2,000 modules in our Android monorepo, Uber’s Mobile Engineering team had to carefully evaluate the impact of adopting something as significant as a new language. To achieve this, we established the following conditions for our model structures: We were in a unique position to perform such a measurement because we generate our network API models and services for Android from Apache Thrift specifications. Additionally,  since code is generated, we can control the morphology of these projects; for instance, we can generate them with only Java code, or only with Kotlin code, a mix between the both of them, and enable or disable annotation processors, among other combinations. informed our decisions for best practices for Android development. We already implemented a flexible plugin system in the code generation to support custom post-processing, so adding the necessary controls to facilitate these new variants was easy. Gradle's unmatched versatility can be relied on to build it all. We already implemented a flexible plugin system in the code generation to support custom post-processing, so adding the necessary controls to facilitate these new variants was easy. Both are free and open-source with support from a wide range of libraries and modules. At Uber, we strive to maintain a modern tech stack in all our applications. While performing this sort of analysis, it is very difficult to cover all the different permutations in which the subject languages could be used. Thales Machado is a senior software engineer on Uber's Amsterdam Mobile Developer Experience team. It is expressive and concise and works with Java. This mainly means going inside our build system and making it issue the metrics we need for this analysis. This can involve inferred return types, lambdas, member references, and generics. Because of this, Kotlin is useful for not only new apps, but also expanding existing Java apps. On average, there are 27 files per project (i.e., the average total files across all 354 projects in the 13 build performance types). Removing the checkers that are not triggered as often and start sharing their classloaders are the immediate actionable items we can take in order to speed up this scenario. By sharing our results and lessons learned, we hope that others can use it to inform their own decisions. The difference between Swift and Kotlin is raw processing performance versus backwards compatibility. To start with Kotlin a good understanding of Java is a must.. Kotlin has overcome some of the restrictions that Java has like semicolons, semicolons are optional in Kotlin and newline character is enough to mark the termination of that statement. It is so robust and fast to work with, and it is written in Kotlin! Figure 2, below, shows the distribution of the generated projects based on their size, as measured by the number of files. This includes surfaces like data class copy()/hashCode()/equals()/toString() functions and destructuring component methods (though this language feature is only useful to Kotlin consumers). To most accurately execute our tests, we needed to leverage non-trivial code we would use in production environments. Kotlin vs Flutter comparison: Performance: One of the main advantages of utilizing Flutter is hot reloading functionality. We wanted to measure pure kotlinc/javac performance, and as such, did not use Kotlin’s. Learn more about Kotlin. We are not sure how big of an impact this implementation has on the Kotlin plus Kapt build performance and could not gather data with the optimized version yet. TypeScript definition generation is only available in the new Kotlin … A platform is an ideal option for developing Android, Desktop, Web, and iOS applications. Kotlin is suitable for database development as it is replacing Java. Java vs Kotlin – In Terms of Performance. An IDE is an application that aids the development of applications. Kotlin language also has … A few other IDEs that you can try are AppCode, Code Runner, and Swifty. . . Having a more diverse representation in terms of project size is imperative for better analysis. Study feasibility of incremental Kapt on Buck. Use the power of non-blocking development without the callback nightmare. Respond Native let us make UI components in JS code which are then translated into the native platform-specific components. The syntax of Swift and that of Kotlin do not resemble each other, though there can be up to 77% string similarity in small chunks of code. Kotlin syntax is also easy to learn for iOS developers because it is based on the same modern concepts they are used to, so your whole team will be able to write cross-platform code efficiently. To declare or not declare the types might be a question that comes up while writing code. One theory we developed for why Apt-powered builds perform so well is because the software is much older and is kept under constant development, which allows for performance optimizations over time, something that has yet to happen with Kapt, since it is a much younger solution. Kotlin is a programming language that is compatible with Android. Many Kotlin developers have called Kotlin “the Swift of Android.” This has helped to create an image for the programming language. This is a good indicator that the experiment environment was well-controlled. It can be also used for backend development using Java frameworks. The most interesting insights are described below: Throughout the 129 experiments, both javac and kotlinc reported consistent times. Understanding how the aforementioned scenarios behave with these features might reveal designs that can boost compilation speeds, and hopefully, lead to discussion on how these tools can be brought to a wider set of build systems. Below, we highlight some additional design considerations and knowledge we had in mind before embarking on this project: Based on these considerations, we created a project generation workflow that enabled us to develop hundreds of models with which to compare build performance for our new Kotlin-based applications. Kotlin shares many similarities with Swift, which is the programming language for iOS. For the project morphology-related data, e.g. This makes mobile application developers interact with the native environment – Swift and XCode for iOS, JavaScript for web, and Kotlin and Android Studio for Android -without using any bridge and deliver codes in a more native way. is still experimental, it adds a number of new improvements. While it is important to keep the project size small so no single project blocks a thread by taking too long to finish and the system can continue to be performant, it is not a concern when it comes to causing exponential growth for individual build times. Buck caches the result of already computed rules to speed up future builds, definitely something you don’t want to do while performing a benchmark to reduce variability between runs. Having a solid pipeline producing data is the best way to understand the impact of new features in your environment. Kotlin Native promises an uncomplicated solution for easily sharing code between Android and iOS. Help is never far away – consult extensive community resources or ask the Kotlin team directly. But this is still not completely implemented on the compiler so it can not be done on Buck just yet. As described in this article, we attempted to leverage our existing infrastructure to run this experiment and test the most scenarios possible (see Table 1). In total, we successfully ran 129 experiments. Buck’s implementation of Kapt is not optimal, as it calls `kotlinc` twice to run annotation processing (once for generating stubs and again for the real annotation processing) and once more for the actual compilation, totaling three calls to `kotlinc`. Android projects may have other considerations such as resources, R classes, android.jar and Android Gradle Plugin. For the project morphology-related data, e.g. Gradle is an open-source build automation tool. Kotlin native (iOS) is currently getting its memory management and concurrency architecture completely redesigned. Capturing this data requires much more effort than the ones presented in this document and would be worth its own article. I recorded some results and i found that swift is faster when the size is around 10000 or less but once the number goes up, Swift becomes significantly slow as compare to Kotlin. A natural progression in the Android space was to start adopting Kotlin, a modern multi-platform programming language and an increasingly popular alternative for Android development that fully interoperates with Java. In iOS, generally, the hooks provided match the lifecycle of the view, creating an intuitive and easy system, and successfully hiding system-level concerns from the developer. Structs/exceptions/unions are generated as standard value types (POJOs). Our build performance data relates to compilation time rather than build time. Kotlin is well-known for being able to achieve more with less code, and our experiments were a testament to this common knowledge. While signing up for an app, a big hassle that may be encountered is the addressing of a large audience. The result? In total, we successfully ran 129 experiments. At least from a build performance perspective, it doesn’t matter whether or not implicit or explicit types are used in the code. Over a million developers have joined DZone. Zac Sweers is a senior software engineer on Uber's Mobile Foundations team. One of its main features is to let users extend its analysis power by adding custom checkers. The Language Stack On top of these developer considerations, we had to ensure that this decision didn’t impact the Uber user experience on our Android apps. Ionic: It tends to support Android 4.4+ versions, iOS 8+ and Windows 10. This project structure results in 1.4 million lines of code (LoC) across 354 different projects that we can compare. Other than that, Apt usage was not as heavy as Kotlin, since the focus of our experiments was Kotlin. Kotlin is 100% interoperable with Java and offers backward compatibility with Java and Android projects. Compiler avoidance/caching mechanisms can vary significantly between build systems, so we decided not to index on it for this project. The original IDE created by Apple is XCode, but there are many alternatives to it. To give a better overview of the generated code, we’ve created a repository with sample code for each of the variants and details of the underlying tech stack. That’s also true for Swift because, apart from already being used in many more platforms, Swift is already being used in web development too. Methods of extension imports and avoiding collisions may differ in various programming languages. Subscribe to our newsletter to keep up with the latest innovations from Uber Engineering. Figure 8: We measured project performance between Pure Kotlin with Kapt (pink) and pure Kotlin (blue) setups, on the left, and pure Java with Apt (brown) and pure Java (turquoise), on the right. It reads from a directory of Thrift specs, infers project dependencies, and then generates a flat set of projects that reflect those specs. Both Swift and Kotlin are interoperable with Java and Objective-C, which makes it possible to use them in new projects and in the maintenance of old ones. This entire process was run in the CI environment every two hours for about two weeks. iOS is superior to Android’s system. The following features make Gradle easy to use: Gradle supports many major IDEs (Integrated Development Environments), including Visual Studio 2017, Android Studio, IntelliJ IDEA, Eclipse, and XCode. Also, annotation processing was designed for Java and can run in-process with the javac compiler, as both share the same AST. … A coroutine is a concurrency design pattern that you can use on Android to simplify code that executes asynchronously.Coroutines were added to Kotlin in version 1.3 and are based on established concepts from other languages.. On Android, coroutines help to manage long-running tasks that might otherwise block the main thread and cause your app to become unresponsive. To declare or not declare the types might be a question that comes up while writing code. Kotlin: Apps built on Kotlin can run on any older Android versions with no issues and iOS 8+ versions. In the end, determining whether or not to adopt a programming language—or a combination of them—requires that you assess their tradeoffs. Running the experiment in a development environment (on a laptop) was not an option. Therefore, the curve seems to be more biased towards the size of the project than by the amount of Java in the project. Also, Kotlin developed apps are easy to customize and better in performance. We believe that the excessive use of this feature, the non-share of their classloader, and poorly written checkers might be the cause of this overhead. , a modern multi-platform programming language and an increasingly popular alternative for Android development that fully interoperates with Java. Teams are smaller in the size and thus easier to manage. We were particularly interested in measuring this after iOS developers observed significant inference penalties in the Swift compiler. Improved performance of Kotlin/Native compilation and execution. number of files, the number of lines that are blank, comments, or code and the number of generated classes and interfaces, we used a mix of the Count Lines of Code (CLoC) CLI and regular expressions, an analysis that looks into the generated project source files and not its compiled bytecode. There are many things that can be done in order to improve Kotlin build performance analysis. They are less verbose, easy to read, and comfortable to work with. This is harder to optimize with Kotlin. Earlier user interfaces (UI) used to be completely XML, which made shifting from Android to iOS very difficult for developers. The syntax of Swift doesn’t just resemble that of Kotlin: in small chunks of code there can be up to 77% string similarity. The natural evolution of software development brings several changes to observed compilation times. Overall, Kotlin resulted in 40 percent fewer lines of source code than Java, Kotlin is well-known for being able to achieve more with less code, and our experiments were a testament to this common knowledge. We named the process of generating the 354 projects for each of the 13 configurations an experiment. On the other hand, Google recommends Kotlin as the standard IDE for Android development. 95 percent have said that they would be willing to accept slower builds if they could write their code in Kotlin. Kotlin Allows iPhone Application Development to Reach Android Users, Developer 5. The “source” in “source code” is also significant here—the Kotlin compiler generates a number of synthetic elements that would otherwise need to be manually included in the equivalent Java source code. Apple has come down hard on the side of creating something optimized and free of most of the chains C/Objective-C. Google (JetBrains, really) has come down equally hard on the side of integrating seamlessly with existing code. Both languages are as concise and transparent as possible. Having an open source data set of projects only increases the range of analysis and unveils better insights. This includes server, client, web, and Android development. This is very advantageous as it provides the level of performance at par with native app development. Learn more. This includes surfaces like data class. There are no measurable and consistent differences between these two programming languages when it comes to their comparison in terms of performance. A majority of cross-platform solutions require you to write all your codes in the target language such as Xamarin. However, our 13 options are still only a subset of what exists out there. This conflates the life cycle of the view with the state of the controller, breaking the fundamental abstraction of MVC. We decided to execute our experiments in our CI machines because these experiments ran so slowly, and our CI boxes were much more powerful than personal machines. As a first step, download the materials for this tutorial by clicking the Download materials button at the top or bottom of the page. We had to agree on a format for the data before shipping it to the database. To support Kapt-less generation, we implemented support for optional direct generation of classes that would otherwise be generated during annotation processing. As this analysis is non-conclusive, we opted to leave it out of this article. This entire process was run in the CI environment every two hours for about two weeks. Swift and Kotlin are two great languages for iOS and Android development respectively. Afterwards, another part of the script was responsible for synchronizing the results repository and shipping the data to our in-house databases, where it could be analyzed. Kotlin is backed by Android Studio and supports the extension function. It is possible to introduce Kotlin into your existing code bases without the need to convert all your existing Java code to Kotlin. See the original article here. The Kotlin community is working on Kotlin multi-platform that will enable you to write code that runs on both iOS and Android. Published at DZone with permission of Navya D. to keep up with the latest innovations from Uber Engineering. Kotlin apps are also faster to build and require fewer resources than native app development. . One way in which Kotlin can be faster than Java is … Buck’s multi-thread build was turned off. The manual trigger of the script would also consume a lot of an engineer’s time and decrease productivity since it prevents them using their laptop for other tasks. To facilitate the success of this adoption, we launched an initiative, in collaboration with JetBrains, to measure Kotlin build performance at scale across different project structures, a process that. While Kotlin’s new type inference system is still experimental, it adds a number of new improvements. Kotlin’s and Swift’s syntax systems are very efficient in that regard and are appreciated by developers for their elegance. Developers who love Java can continue using it, and also add Kotlin code incrementally and make use of Kotlin libraries. Currently this is only implemented in Gradle, but it may be a possible area to improve compilation speeds on Buck projects as well with using Kapt. Introducing Base Web, Uber’s New Design System for Building Websites in... ETA Phone Home: How Uber Engineers an Efficient Route, Announcing Uber Engineering’s Open Source Site. To run our experiment, we took the following steps: A Python script orchestrated the experiment execution; the language of choice for this type of experiment has no impact on experiment performance and was chosen based on team familiarity. Based on configurability, we came up with a matrix of 13 different scenarios for fine-grained understanding of different project structures and tooling tradeoffs: We named the process of generating the 354 projects for each of the 13 configurations an experiment. The big benefit of React Native is the huge community and great adoption … One of its main features is to let users extend its analysis power by adding custom checkers. iven our stack’s usage of Buck, we leverage. Namely, support for generating. For this number, Kotlin is almost 18 times faster than Swift(on my machine). Tho Nguyen is a senior software engineer on Uber's Amsterdam Mobile Developer Experience team. By using native controls and native modules, React Native improves on performance. In this table, the displayed compilation time for line one represents the average compilation time across all 354 projects for all experiment runs. Opinions expressed by DZone contributors are their own. Other than that, they need a good bit of boilerplate to communicate with the platform code such as React Native. In terms of typing, both Kotlin and Swift are strong and static and they both allow work with dynamic types. We believe that this happens due to the following reasons: Even with these reasons, it is odd to see that pure Java plus Apt is much faster when compared to pure Java with no Apt (only a ~5 percent overhead). The analysis aggregated the data in buckets based on the build performance matrix (Table 1). By doing so, it uses a specific thread from UI, which causes an increase in performance. To support Kapt-less generation, we implemented support for optional direct generation of classes that would otherwise be generated during annotation processing. I tried sorting an array of size 100000000 in Swift and Kotlin and i can see a huge performance gap between them. The JavaScript target for Kotlin has a new Gradle DSL and an alpha version of the Kotlin/JS IR compiler back end. With that in mind, we did not want to rely on results that would be improved only by using those features. We chose ElasticSearch and Kibana for this experiment as the visualizations that we wanted could be better built in it. Our standard model generation pipeline is a simple command line interface around a project generator. 4. Many of the users may use similar usernames to log in. There is obviously no simple answer for the question of whether or not Kotlin is right for your project or team. We generate one project per .thrift file, and projects can depend on other generated projects that match the Thrift “include” statements. to wrap the Buck usage. It is in Buck’s vision to not support incremental compilation, as it results in compilation states that are harder to reproduce (imagine the steps to reproduce a compilation failure having a lot of Git patches intertwined with build commands).

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