DroidCC: A Scalable Clone Detection Approach for Android Applications to Detect Similarity at Source Code Level

Android became more popular and widely used operating system. It has been noticed that the code clones in Android apps make it difficult to maintain the security flaws in source code. To avoid these problems, it is essential to find, identify, evaluate and recover those code clones as early as possible. In this paper, we propose and design DroidCC, a novel clone detection approach in Android applications, that helps to detect different types of clones from APK's source code. A prototype has been developed and implemented on the dataset of almost 30,000 top rated Android apps. DroidCC detects type-1, type-2 and type-3 clones in Android apps at the source code level. It also detects the similar code fragments, that were injected into many applications, which might be an indication of spreading malware. Meanwhile it can detect full and partial level similarity between applications. We evaluate DroidCC clone detection approach on real time data-set and count the Recall and Precision, which is quite significant. Furthermore, our results show that our approach is very efficient and effective in detecting different types of clones to check the similarity level in Android applications.