Android: Unit Testing Apps with Couchbase, Robolectric and Dagger

This Android / Gradle project on GitHub shows how to integrate Couchbase, Robolectric and Dagger so that unit testing can occur without the need for a connected device or emulator.


I need a database for my TripComputer app so that users can keep a log of their Journeys. I could use SQL Lite, but I prefer not to use SQL if possible. With SQL you’re forced to maintain a fixed schema and SQL Lite doesn’t offer any out of the box cloud replication capabilities, unlike most NoSQL databases.

Couchbase Lite for Android is an exciting new embedded NoSQL database, but because its ‘Database’ and ‘Manager’ classes are Final and require native code, it’s not trivial to mock them or integrate them into apps that utilise the popular Robolectric testing framework.

Therefore, in order to support off-device Java VM based testing with Robolectric it is necessary to write custom interfaces and use a dependency injection framework that will allow the injection of mock objects to occur when testing. To achieve this ‘dependency injection’ of mocks, I’ve used Mockito and introduced the Dagger framework into the code.

Software Versions

  1. Couchbase-lite
  2. Robolectric 2.4
  3. Dagger 1.2.2
  4. Mockito 1.10.19
  5. Android Studio 1.1 Beta 3 (optional)

About The Sample App

The App I’ve built here is very simple. When the user clicks the Save button on the screen, in the background a new document (technically a `java.util.Map`) is created and saved to the embedded Couchbase NoSQL database. While saving the new document, Couchbase automatically assigns it an ID and it is this ID that is ultimately displayed to the user on the screen after they’ve clicked the Save button. The document id’s in Couchbase take the form of GUID’s.

The App Code

Roughly speaking, in the `app` codebase you’ll see the following…

1. `` is a simple Android action bar activity that extends a `BaseActivity` and requires a `PersistanceManager` to be injected at runtime so it can talk to the database.

2. `` is a class that acts as a DAO object to `MyActivity`, managing the persistence of ‘Map’ objects. It offers only INSERT and GET operations in this sample and requires a `PersistanceAdapter` implementation to be injected into it.

3. `` is an interface that defines INSERT and GET operations on `Map` objects. This interface is required later when mocking & testing.

4. `` is a concrete implementation of the `PersistanceAdapter` interface. It utilises Couchbase and depends on a couchbase `Database` object which must be constructed by Dagger and injected into it.

5. The injectable objects that require non-trivial instantiation (like the Couchbase `Database` object for example) are defined by `@Provides` methods in a Dagger `@Module` in the `MyActivityModule` class.

At runtime, Dagger, `MyActivity`, `BaseActivity` and the `App` application classes take care of constructing an `ObjectGraph` for the application and inserting the required dependencies so that all the various `@Inject` requirements can be met. The “Instrumentation (integration) Tests” in the Android App gradle project test that this integration and dependency injection is working as expected.

The Robolectric Tests

Because it’s also desirable to perform testing without a device or emulator, there’s a set of Robolectric tests for the App’s `MyActivity` class that test the same ‘Save’ feature but without the need for a connected or emulated device and without the need for an embedded Couchbase database.

In the `app-test` gradle project you’ll see the following…

1. `` extends the MyActivity class and `@Overrides` the `getModules()` method. This method constructs and returns a `TestMyActivityModule` instance. `TestMyActivityModule` is an inner class which defines an alternative (overriding) Dagger `@Module` that can also provide a `PersistanceManager` for injection into the `MyTestActivity` when testing. This module `@Provides` a fake, programmable `PersistenceManager` _mock_, not a real persistance manager as is expected under normal conditions.

2. `` is a standard Robolectric test, but it’s Robolectric controller builds a new `MyTestActivity`. The method `testClickingSaveButtonSavesMapAndDisplaysId()` tests that clicking the _Save_ button has the required affect by pre-programming the `PersistenceManager` mock with behaviours and then verifying that this mock has indeed been called by the Activity as expected.

Running the Sample

To run the tests for yourself just clone or download this repository and then execute the following gradle commands. For completeness, I’ve included some Android Instrumentation Tests as well and you can run them with `gradlew connectedCheck` (assuming an emulator or device is present).

gradlew clean
gradlew assemble
gradlew check
gradlew connectedCheck (this is optional and assumes a device is present)


Many thanks to Andy Dennie for his Dagger examples on GitHub. These were really helpful to this Dagger noob when trying to understand how to integrate Dagger with Android.

About the Author

Ben Wilcock is the developer of TripComputer, the only distance tracking app for Android with a battery-saving LOW POWER mode. It’s perfect for cyclists, runners, walkers, hand-gliders, pilots and drivers. It’s free! Download it from the Google Play Store now:- Get the App on Google Play

You can connect with Ben via his Blog, Website, Twitter or LinkedIn.

Implementing Entity Services using NoSQL – Part 5: Improving autonomy using the Cloud

In the previous posts I discussed how I went about building my SOA ‘Entity’ service for Products by using a combination of Java Web Services, Java EE and the CouchDB NoSQL database. In this final post in the series I’m going to leverage some of the technical assets that I’ve created and implement some new user stories using some popular SOA patterns.

My current Product Entity Service implementation is very business process agnostic, and therefore highly re-usable in any scenario where consumers want to discover or store Product information. However, as it stands the Product Entity Service is designed to be used within a trusted environment. This means that there are no restrictions on access to operations like Create, Update or Delete.  This is fine within a strictly controlled corporate sandbox but what if I want to share some of my service operations or Product information with non trusted users?

Lets imagine that in addition to our in-house use of the Product Entity Service we also wanted to cater for the following agile ‘user story’…


Implementing Entity Services using NoSQL – Part 3: CouchDB

Following on from part two of this series where I created and deployed the Product Entity Service using the SOA ‘contract-first’ technique, I’m now going to work on the NoSQL database aspects of the service implementation.


Implementing Entity Services using NoSQL – Part 2: Contract-first

It’s time to begin the coding of my SOA entity service with NoSQL project, and as promised I’m starting with the web service’s contract.

This technique of starting with a web service contract definition is at the heart of the ‘contract-first’ approach to service-oriented architecture implementation and has numerous technical benefits including…


Implementing Entity Services using NoSQL – Part 1: Outline

Over the past few weeks I’ve been doing some R&D into the advantages of using NoSQL databases to implement Entity services (also known as Data Services).

Entity service is a classification of service coined in the Service Technology series of books from Thomas Erl. It’s used to describe services that are highly agnostic and reusable because they deal primarily with the persistence of information modelled as business data ‘entities’. The ultimate benefit of having thin layer of these entity services is in the ease at which you can re-use them to support more complex service compositions.

This approach is further described in the Entity Abstraction SOA pattern.

Entity service layers are therefore a popular architectural choice in SOA, and implementing them has meant big business for vendors like Oracle and IBM, both of whom offer software to support this very task. There is even a separate standard for technologies in this area called Service Data Objects (or SDO for short).

This is all well and good, but these applications come with dedicated servers and specialised IDE’s and its all a bit ‘heavyweight’. These specialised solutions can be terribly expensive if all you really want are some simple CRUD-F operations (Create, Read, Update, Delete, Find) on a service that manages the persistence of a simple canonical data type like a Product or a Customer.