Applications (apps) in Android can be developed using either MIT’s App Inventor 2 (AI) [3]or by using IDEs such as Android Studio (AS) [1]with the help of Android SDK. MIT’s AIis the second version of the Google’s original App Inventor, whichis a web browser based development environment forasimplerway to develop android apps. With little to no knowledge of programming,one can developand deployan android appusing AI.However, this simplicity comes at aprice;AI does not provide all of Android’s advanced features and most apps developed in AI have to follow a specific design template.To accessallof Android’s features, one needs to develop apps using tools such as Android Studio, which is provided by Google as a full-fledgeddevelopment environment for Android development, debugging, testing, and packaging. While communications between any two Android appsdeveloped in either AI or AS arefairly straightforward; apps developed by these two development platformseparately do not have a similarway to communicatewith each other. To define the problem, supposewe have two AI apps AI1and AI2,along with two AS apps AS1, AS2. Now also consider, P1is the process through which AI1communicateswith AI2and P2is the process through which AS1communicateswith AS2. Then it is known that P1 ≠P2.This resultsinno established process, Px, that will allow apps developed by AS tocommunicate with apps developed by AI. This paper will present thisprocess Px, which will allow apps developed in two different platforms to communicate with each other programmatically.Obvious questions arise,asto why we need to generate this process given that AI apps do not have advanced features. Since AI provides faster lead time in developing apps than AS, having a back end system developed by AS on which AI app scan run,would give developers afaster way of developing new app ecosystems. One such situation is presented below.Since 2013, Winston-Salem State University has begun implementing a Mobile Response System (MRS) [4]-[6]. MRSis a mobile learning environment that enhances class room engagement by creating a responsive environment where students solve problems in an interactive way that communicates solutions directly and immediately to their instructor. This is performed through Android powered mobile devices, which have interactive activities in which students learn principles of their subject with immediate feedback.Thismobile platform is used by the faculty to develop their own interactive activities to be used in the classroom.However, currently, such interactive activities must be developed by AS to be usedwith MRS. One way to alleviate this problem is to allow the MRS to communicate with apps developed by both AI and AS. That way, interactive apps developed by faculty from other disciplines using AI can utilize MRS to deploy their activities in the class. codeshoppy
his paper presents a technique to provide Android inter-app communications when apps are developed in two different development platforms:Android Studio and AppInventor. Performance data was provided and methods were compared to find any limitations. In the future, the presented technique will be used to extend MRS to other disciplines and will shed more light into how larger and more complex apps will work together when they are designed by two different Android development platforms.
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