As of 2024 we still believe that we made the right choice back in 2015 of Android SDK as the basis for our Android application.

Nowadays, we could choose from plenty of cross-platform SDK options, which would’ve probably saved us resources at the beginning of the product’s development life cycle. However, engineering resource utilization isn’t the only consideration for making decisions. If you wanted to create the best women’s health solution on the market, you would need to care about performance and seamless integration with operating system features too. The modern cross-platform SDKs have just begun to get closer to the native development option in that regard. The Kotlin Multiplatform Project is a good example of such a framework. Unfortunately, because it hasn't been around for a long time, it still has plenty of issues, so it currently doesn't fit our needs. However, we might consider it in the future. All in all, I believe that we made the right choice.

Over time, Android engineering best practices, tools, and the operating system itself evolved, giving developers multiple ways to implement the same features more effectively, both in terms of engineering team performance and device resource utilization. Our team evolved as well: We’ve come a long way from a single Android developer to a dozen feature teams that need to work on the same codebase simultaneously without stepping on each other's toes. We began caring more about cycle time because one can’t successfully compete by delivering value slowly.

For our dev team, these changes prompted a request to update the codebase in order to deliver value faster and increase the speed of new Android features adoption, raising the overall level of quality at the same time.

We began with the modularization of our Android application. Using the power of the Gradle build system, we split our application into 70+ shared core modules and 30+ independent feature modules. Such a huge step required the revision of the application’s architecture. One could say that we moved to clean architecture; however, I would say that we use architecture driven by common software engineering principles like SOLID, DRY, KISS, etc. On the presentation layer, we switched from the MVP to the MVVM pattern. Implementation of this pattern, powered by the Jetpack Lifecycle components, simplifies Android component lifecycle management and increases the reusability of the code.

Supporting such a setup would be barely possible without a dependency injection (DI) implementation. We settled on Dagger 2. This DI framework supports compile-time graph validation, multibinding, and scoping support. Apart from that, it offers two ways to wire up individual components into a single graph: subcomponents and component dependencies, each good for its purpose. At Flo, we prefer component dependencies, as they better isolate the features and positively impact the build speed, but we use subcomponents closer to the leaves of the dependency graph as well.

Though we still have Java code in the project, Kotlin has become our main programming language. Compared to Java, it has multiple advantages:

Improved type system, which, for example, makes it possible to avoid the “billion-dollar mistake” in the majority of cases
Rich and mature standard library, which provides solutions for many typical tasks out of the box and minimizes the need for extra utilities
Advanced features to better fit the open-closed principle (for example, extension functions and removal of checked exceptions let us improve the extendability of solutions)
The syntax sugar, which simply lets you write code faster (it’s hard to imagine modern Android development without data classes, sealed classes, delegates, etc.) We attempt to use Kotlin wherever possible. Our build scripts are written in it, and we also migrate the good old bash scripts onto KScript.

Another huge step in Kotlin adoption is the migration from RxJava to the Kotlin coroutines. RxJava is a superb framework for event-based and asynchronous programming. However, it is not the best choice for asynchronous programming. In that regard, Kotlin coroutines seem like a much wiser choice, offering more effective resource utilization, more readable error stack traces, finer control over the execution scope and the syntax, which looks almost identical to the synchronous code. In its main area of usage — event-based programming — RxJava has also begun to lose ground. Being written in Java, it does not support Kotlin’s type system well. Besides, many of its operators are synchronous by design, which can limit developers. Driven by the Kotlin coroutines, Flow addresses both of these drawbacks and we found it perfectly fits our needs.

Perhaps the most noticeable sign that the above changes were not taken in vain is that you can now use Flo on your smartwatch powered by Android Wear. This is the second Flo app for the Android platform, and it effectively reuses the codebase of the mobile app. One of the core advantages of the Flo Watch app lies in Wear Health Services. It allows us to effectively and securely collect health-related data from the user’s device, if a user so chooses, and utilize it to improve the precision of cycle estimation.

But we won't stop chasing innovation!

Even though we migrated to ViewBinding, enjoying the extra type safety and reduced amount of the boilerplate code, we couldn’t pass by the Jetpack Compose framework. It allows us to use Kotlin power to construct UI, reduces code duplication, increases reusability of the UI components, and unblocks building complex view hierarchies with less performance penalty.

Finally, what about recent Android features support? Well, we continuously improve the app in that sense. Like most teams, we rely on different Jetpack, Firebase, and Play Services libraries to achieve that goal. We use them to move work to the background, implement push notifications, integrate billing, and many other little things, all of which improve the overall UX or let us reach out to users more effectively. However, we also invest in first-party tooling. In an effort to ensure secure and transparent management of user data, we implemented our own solutions for A/B testing, remote configuration management, logging, and analytics.

What about quality? Developers are responsible for the quality of created solutions. To ensure that we use modern tools and approaches:

We chose Detekt and Android Lint for static code analysis. These frameworks prevent many issues from coming up in production by analyzing the codebase during compile time. They are capable of finding the most common problems in Kotlin and Android-related code, ensuring the whole team follows the same code style. When those frameworks do not provide the necessary checks out of the box, we implement them by ourselves.
The above two frameworks are used both locally and in the continuous integration pipelines. However, in the latter, we additionally utilize the Sonarcloud tool. It provides extended complexity, security, and potential bug checks, which are run in the cloud.
To ensure that the code meets the requirements, we use multiple layers of automated testing. Our test pyramid includes unit tests, which use the JUnit5 platform, and E2E tests powered by Espresso framework. Together, these two approaches to testing allow developers to get feedback fast while at the same time ensuring that features work as expected end-to-end.

Flo Health Tech Stack