Abstracts

When developing mobile applications, the tradition has been to write code specific (native) for each platform they are running on. Usually its about writing two separate applications for the biggest platforms, Android and iOS. There exist alternatives to this approach that uses the same code for different platforms. React Native is a relatively new cross-platform development framework that makes it possible to use the same code for application to Android and iOS. It also uses native UI-elements as a possible solution for performance issues that is often associated with cross-plattform development. This thesis evaluates React Native and compares it against native Android. The implementation is done by replicating the main functionality from a social media application written as a native Android application. However, the application is not made as an exact replica since that could limit the solutions in React Native. The evaluation is done in a Startup company and therefore focuses on aspects important in a Startup. Another issue when developing a mobile application is what type of backend that shall be used. Performance, scalability and complexity are all important aspects when choosing a framework or language as a base for the backend architecture.There do exist theoretical frameworks that could be used when building the backend. However, these frameworks require resources that are often missing in a Startup. AWS Lambda is a platform that claims to be a cost-effective way of building a scalable application. In this thesis AWS Lambda is evaluated to see if it can be used to create an automatically scaled backend for this type of social media application. The conclusion of the React Native evaluation is that it can be a suitable alternative to native Android development. If the team has previous experience in web development but lack experience in mobile application development it can be a wise choice since it removes the need to learn two frameworks in native Android and native iOS development. React Native is also good to fast create functional prototypes which can be shown to potential investors. The biggest drawback is performance in animations. However, there are often ways to work around that. In our case this drawback did not affect the user experience of the end application. The evaluation of AWS Lambda concludes that it is not for every project. In this thesis, the application was a bit too database heavy and therefore the autoscaling ability did not work properly. However, for a service that needs a lot of computing power, AWS Lambda could be a good fit. It could also be a suitable alternative if someone in the team has previous experience in the AWS environment.