Toward interactive bug reporting for (android app) end-users

Abstract

This paper introduces BURT, a web-based chatbot for interactive reporting of Android app bugs. BURT is designed to assist Android app end-users in reporting high-quality defect information using an interactive interface. BURT guides the users in reporting essential bug report elements, i.e., the observed behavior, expected behavior, and the steps to reproduce the bug. It verifies the quality of the text written by the user and provides instant feedback. In addition, BURT provides graphical suggestions that the users can choose as alternatives to textual descriptions.We empirically evaluated BURT, asking end-users to report bugs from six Android apps. The reporters found that BURT's guidance and automated suggestions and clarifications are useful and BURT is easy to use. BURT is an open-source tool, available at github.com/sea-lab-wm/burt/tree/tool-demo.A video showing the full capabilities of BURT can be found at https://youtu.be/SyfOXpHYGRo.

Analyzing the impact of API changes on Android apps

“…To enhance software maintenance tasks, the acquisition of highquality bug reports and the automated identification of buggy code locations can significantly expedite bug understanding, reproduction, and resolution processes. The design of our research draws inspiration from successful results from the development of an interactive bug reporting system [28,29], as well as leveraging GUIs for automatically identifying buggy locations in source code [20],…”

“…Our research instantiated with designing an interactive BUg Re-porTing (BURT) system [28,29], which guides users while reporting bugs, assesses the quality of the bug report elements, provides feedback to the reporters, suggests graphical contents during reporting, and generates high-quality bug reports. The entire bugreporting system comprises three components: 2.1.1 Natural Language Parser (NL).…”

“…In this phase, we generate an execution model of the application using established research strategies [10,28,29]. We also extract actions, primitives, and objects [16] using prompt engineering.…”

“…The inadequacies of existing bug reporting systems are evident in their failure to bridge the lexical gap between end-users and developers [22,35]. Existing bug reporting systems (i) offer limited guidance on the contents and the presentation of those contents in bug reports and (ii) lack mechanisms to provide feedback to reporters regarding the correctness and completeness of the bug report information [28,29]. Consequently, due to the static nature of these bug-reporting interfaces, the responsibility of furnishing high-quality information falls on the shoulders of the reporters.…”

Automatically Reproducing Android Bug Reports Using Natural Language Processing and Reinforcement Learning

“…Fazzini et al proposed EBUG [22] to assist reporters to write more accurate reproduction steps by using information from static and dynamic analysis of the AUT to predict the next step. Yang et al proposed an interactive bug reporting system, BURT [35], which provides a guided reporting of essential bug report elements (i.e., the observed behavior, expected behavior, and steps to reproduce the bug), instant feedback of problems with the elements, and graphical suggestions of the said elements. These three approaches mainly help improve the quality of the bug report at the moment when users write the report, but do not reproduce them.…”