A Model for Diagnosing the Largest Number of Android Application Problems, based on Reviews in Download Stores by Use of the Decision Tree

Raed Kazem Mohsen and Ahmed Saleem Abbas

Mobile applications play a pivotal role in the daily life of the user, where millions of customers rely on smartphone applications for the purpose of social networking, banking, news and many other uses, with the ability to use it anytime and anywhere and in most conditions. So that software engineers‟ race to Create and provide the applications to customer service. However, despite good planning processes for software engineers in designing and building applications, the product may be accompanied by some errors that may lead to a malfunction in the application or one of its functions, which requires performing maintenance for it, and often that difficult and costly, in addition to the possibility of repeating the process whenever new problems in the application are discovered. It is therefore essential to look for ways to diagnose application performance issues and detect as many errors in Android apps as possible to avoid repetitive maintenance, and focus on tools that help build good apps with minimal "Effort", "Time" and "Cost”. This paper contributes to the detection of errors and performance problems in Android applications and the diagnosis of problems by used the user‟s feedback within download platforms.

Volume 12 | Issue 4

Pages: 237-246

DOI: 10.5373/JARDCS/V12I4/20201438