An Empirical Study on Leveraging Images in Automated Bug Report Reproduction
Automated bug reproduction is a challenging task, with existing tools typically relying on textual steps-to-reproduce, videos, or crash logs in bug reports as input. However, images provided in bug reports had been overlooked. To address this gap, this paper presents an empirical study investigating the necessity of including images as part of the input in automated bug reproduction. We examined the characteristics and patterns of images in bug reports, focusing on (1) the distribution and types of images (e.g., UI screenshots), (2) documentation patterns associated with images (e.g., accompanying text, annotations), and (3) the functional roles they served, particularly their contribution to reproducing bugs. Furthermore, we analyzed the impact of images on the performance of existing tools, identifying the reasons behind their influence and the ways in which they can be leveraged to improve bug reproduction. Our findings reveals several new interesting findings which proved the importance of images in supporting automated bug reproduction. Specifically, we identified six distinct functional roles that images serve in bug reports, each exhibiting unique patterns and specific contributions to the bug reproduction process. This study offers new insights into tool advancement and suggest promising directions for future research.
Mon 28 AprDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:30 | Defects, bugs, and issuesData and Tool Showcase Track / Technical Papers / Registered Reports at 214 Chair(s): Minhaz Zibran Idaho State University | ||
11:00 10mTalk | Learning from Mistakes: Understanding Ad-hoc Logs through Analyzing Accidental Commits Technical Papers Yi-Hung Chou University of California, Irvine, Yiyang Min Amazon, April Wang ETH Zürich, James Jones University of California at Irvine Pre-print | ||
11:10 10mTalk | On the calibration of Just-in-time Defect Prediction Technical Papers Xhulja Shahini paluno - University of Duisburg-Essen, Jone Bartel University of Duisburg-Essen, paluno, Klaus Pohl University of Duisburg-Essen, paluno | ||
11:20 10mTalk | An Empirical Study on Leveraging Images in Automated Bug Report Reproduction Technical Papers Dingbang Wang University of Connecticut, Zhaoxu Zhang University of Southern California, Sidong Feng Monash University, William G.J. Halfond University of Southern California, Tingting Yu University of Connecticut | ||
11:30 10mTalk | It’s About Time: An Empirical Study of Date and Time Bugs in Open-Source Python Software Technical Papers Shrey Tiwari Carnegie Mellon University, Serena Chen University of California, San Diego, Alexander Joukov Stony Brook University, Peter Vandervelde University of California, Santa Barbara, Ao Li Carnegie Mellon University, Rohan Padhye Carnegie Mellon University | ||
11:40 10mTalk | Enhancing Just-In-Time Defect Prediction Models with Developer-Centric Features Technical Papers Emanuela Guglielmi University of Molise, Andrea D'Aguanno University of Molise, Rocco Oliveto University of Molise, Simone Scalabrino University of Molise | ||
11:50 10mTalk | Revisiting Defects4J for Fault Localization in Diverse Development Scenarios Technical Papers Md Nakhla Rafi Concordia University, An Ran Chen University of Alberta, Tse-Hsun (Peter) Chen Concordia University, Shaohua Wang Central University of Finance and Economics | ||
12:00 5mTalk | Mining Bug Repositories for Multi-Fault Programs Data and Tool Showcase Track | ||
12:05 5mTalk | HaPy-Bug - Human Annotated Python Bug Resolution Dataset Data and Tool Showcase Track Piotr Przymus Nicolaus Copernicus University in Toruń, Poland, Mikołaj Fejzer Nicolaus Copernicus University in Toruń, Jakub Narębski Nicolaus Copernicus University in Toruń, Radosław Woźniak Nicolaus Copernicus University in Toruń, Łukasz Halada University of Wrocław, Poland, Aleksander Kazecki Nicolaus Copernicus University in Toruń, Mykhailo Molchanov Igor Sikorsky Kyiv Polytechnic Institute, Ukraine, Krzysztof Stencel University of Warsaw Pre-print | ||
12:10 5mTalk | SPRINT: An Assistant for Issue Report Management Data and Tool Showcase Track Pre-print | ||
12:15 5mTalk | Identifying and Replicating Code Patterns Driving Performance Regressions in Software Systems Registered Reports Denivan Campos University of Molise, Luana Martins University of Salerno, Emanuela Guglielmi University of Molise, Michele Tucci University of L'Aquila, Daniele Di Pompeo University of L'Aquila, Simone Scalabrino University of Molise, Vittorio Cortellessa University of L'Aquila, Dario Di Nucci University of Salerno, Rocco Oliveto University of Molise | ||