Abstract: The mobile applications industry experiences an unprecedented high growth, developers working in this context face a fierce competition in acquiring and retaining users. They have to quickly implement new features and fix bugs, or risks losing their users to the competition. The only way for them to achieve this goal is by closely monitoring the user feedback they receive in form of reviews. However, successful apps can receive up to several thousands of reviews per day, manually analysing each of them is a time consuming task. To help developers deal with the large amount of available information, we have developed a novel approach, called URR (User Request Referencer), that is able to organise reviews according to predefined fine grained maintenance and evolution tasks (battery, performance, memory, privacy, etc.) and recommend the related source code artifacts. We evaluated our approach through an empirical study involving the reviews and code of 39 mobile applications. Our results show a high precision and recall of URR in organising reviews according to predefined maintenance and evolution tasks and recommending the source code files that need to be modified to handle the issues raised by users in their reviews. Finally, during the evaluation we discovered that using information concerning the organization of mobile software projects improves the source code localization results. This repository provides the replication package with (i) material and working data sets of our study, (ii) complete results of the SURVEY; and (iii) rawdata for replication purposes and to support future studies. A detailed description of the contents is included in README.txt.