Prompting Is All Your Need: Automated Android Bug Replay with Large Language Models

Bug reports are vital for software maintenance that allow users to inform developers of the problems encountered while using the software. As such, researchers have committed considerable resources toward automating bug replay to expedite the process of software maintenance. Nonetheless, the success of current automated approaches is largely dictated by the characteristics and quality of bug reports, as they are constrained by the limitations of manually-crafted patterns and pre-defined vocabulary lists. Inspired by the success of Large Language Models (LLMs) in natural language understanding, we propose AdbGPT, a new lightweight approach to automatically reproduce the bugs from bug reports through prompt engineering, without any training and hard-coding effort. AdbGPT leverages few-shot learning and chain-of-thought reasoning to elicit human knowledge and logical reasoning from LLMs to accomplish the bug replay in a manner similar to a developer. Our evaluations demonstrate the effectiveness and efficiency of our AdbGPT to reproduce 81.3% of bug reports in 253.6 seconds, outperforming the state-of-the-art baselines and ablation studies. We also conduct a small-scale user study to confirm the usefulness of AdbGPT in enhancing developers' bug replay capabilities.Comment: Accepted to 46th International Conference on Software Engineering (ICSE 2024

Efficiency Matters: Speeding Up Automated Testing with GUI Rendering Inference

Due to the importance of Android app quality assurance, many automated GUI testing tools have been developed. Although the test algorithms have been improved, the impact of GUI rendering has been overlooked. On the one hand, setting a long waiting time to execute events on fully rendered GUIs slows down the testing process. On the other hand, setting a short waiting time will cause the events to execute on partially rendered GUIs, which negatively affects the testing effectiveness. An optimal waiting time should strike a balance between effectiveness and efficiency. We propose AdaT, a lightweight image-based approach to dynamically adjust the inter-event time based on GUI rendering state. Given the real-time streaming on the GUI, AdaT presents a deep learning model to infer the rendering state, and synchronizes with the testing tool to schedule the next event when the GUI is fully rendered. The evaluations demonstrate the accuracy, efficiency, and effectiveness of our approach. We also integrate our approach with the existing automated testing tool to demonstrate the usefulness of AdaT in covering more activities and executing more events on fully rendered GUIs.Comment: Proceedings of the 45th International Conference on Software Engineerin

Towards Efficient Record and Replay: A Case Study in WeChat

WeChat, a widely-used messenger app boasting over 1 billion monthly active users, requires effective app quality assurance for its complex features. Record-and-replay tools are crucial in achieving this goal. Despite the extensive development of these tools, the impact of waiting time between replay events has been largely overlooked. On one hand, a long waiting time for executing replay events on fully-rendered GUIs slows down the process. On the other hand, a short waiting time can lead to events executing on partially-rendered GUIs, negatively affecting replay effectiveness. An optimal waiting time should strike a balance between effectiveness and efficiency. We introduce WeReplay, a lightweight image-based approach that dynamically adjusts inter-event time based on the GUI rendering state. Given the real-time streaming on the GUI, WeReplay employs a deep learning model to infer the rendering state and synchronize with the replaying tool, scheduling the next event when the GUI is fully rendered. Our evaluation shows that our model achieves 92.1% precision and 93.3% recall in discerning GUI rendering states in the WeChat app. Through assessing the performance in replaying 23 common WeChat usage scenarios, WeReplay successfully replays all scenarios on the same and different devices more efficiently than the state-of-the-practice baselines

Altered exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of cultured striatal neurons in a knock-in mouse model of Huntington’s disease

Huntington’s disease (HD) is a progressive dominantly inherited neurodegenerative disease caused by the expansion of a cytosine-adenine-guanine (CAG) trinucleotide repeat in the huntingtin gene, which encodes the mutant huntingtin protein containing an expanded polyglutamine tract. One of neuropathologic hallmarks of HD is selective degeneration in the striatum. Mechanisms underlying selective neurodegeneration in the striatum of HD remain elusive. Neurodegeneration is suggested to be preceded by abnormal synaptic transmission at the early stage of HD. However, how mutant huntingtin protein affects synaptic vesicle exocytosis at single presynaptic terminals of HD striatal neurons is poorly understood. Here, we measured synaptic vesicle exocytosis at single presynaptic terminals of cultured striatal neurons (mainly inhibitory neurons) in a knock-in mouse model of HD (zQ175) during electrical field stimulation using real-time imaging of FM 1-43 (a lipophilic dye). We found a significant decrease in bouton density and exocytosis of synaptic vesicles at single presynaptic terminals in cultured striatal neurons. Real-time imaging of VGAT-CypHer5E (a pH sensitive dye conjugated to an antibody against vesicular GABA transporter (VGAT)) for inhibitory synaptic vesicles revealed a reduction in bouton density and exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of HD striatal neurons. Thus, our results suggest that the mutant huntingtin protein decreases bouton density and exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of striatal neurons, causing impaired inhibitory synaptic transmission, eventually leading to the neurodegeneration in the striatum of HD

Role of ST-Segment Resolution Alone and in Combination With TIMI Flow After Primary Percutaneous Coronary Intervention for ST-Segment–Elevation Myocardial Infarction

BACKGROUND: To evaluate the role of ST-segment resolution (STR) alone and in combination with Thrombolysis in Myocardial Infarction (TIMI) flow in reperfusion evaluation after primary percutaneous coronary intervention (PPCI) for ST-segment– elevation myocardial infarction by investigating the long-term prognostic impact.METHODS AND RESULTS: From January 2013 through September 2014, we studied 5966 patients with ST-segment–elevation myocardial infarction enrolled in the CAMI (China Acute Myocardial Infarction) registry with available data of STR evaluated at 120 minutes after PPCI. Successful STR included STR ≥50% and complete STR (ST-segment back to the equipotential line). After PPCI, the TIMI flow was assessed. The primary outcome was 2-year all-cause mortality. STR &lt; 50%, STR ≥50%, and complete STR occurred in 20.6%, 64.3%, and 15.1% of patients, respectively. By multivariable analysis, STR ≥50% (5.6%; adjusted hazard ratio [HR], 0.45 [95% CI, 0.36–0.56]) and complete STR (5.1%; adjusted HR, 0.48 [95% CI, 0.34–0.67]) were significantly associated with lower 2-year mortality than STR &lt;50% (11.7%). Successful STR was an independent predictor of 2-year mortality across the spectrum of clinical variables. After combining TIMI flow with STR, different 2-year mortality was observed in subgroups, with the lowest in successful STR and TIMI 3 flow, intermediate when either of these measures was reduced, and highest when both were abnormal.CONCLUSIONS: Post-PPCI STR is a robust long-term prognosticator for ST-segment–elevation myocardial infarction, whereas the integrated analysis of STR plus TIMI flow yields incremental prognostic information beyond either measure alone, support-ing it as a convenient and reliable surrogate end point for defining successful PPCI.</p

Role of ST-Segment Resolution Alone and in Combination With TIMI Flow After Primary Percutaneous Coronary Intervention for ST-Segment–Elevation Myocardial Infarction

BACKGROUND: To evaluate the role of ST-segment resolution (STR) alone and in combination with Thrombolysis in Myocardial Infarction (TIMI) flow in reperfusion evaluation after primary percutaneous coronary intervention (PPCI) for ST-segment– elevation myocardial infarction by investigating the long-term prognostic impact.METHODS AND RESULTS: From January 2013 through September 2014, we studied 5966 patients with ST-segment–elevation myocardial infarction enrolled in the CAMI (China Acute Myocardial Infarction) registry with available data of STR evaluated at 120 minutes after PPCI. Successful STR included STR ≥50% and complete STR (ST-segment back to the equipotential line). After PPCI, the TIMI flow was assessed. The primary outcome was 2-year all-cause mortality. STR &lt; 50%, STR ≥50%, and complete STR occurred in 20.6%, 64.3%, and 15.1% of patients, respectively. By multivariable analysis, STR ≥50% (5.6%; adjusted hazard ratio [HR], 0.45 [95% CI, 0.36–0.56]) and complete STR (5.1%; adjusted HR, 0.48 [95% CI, 0.34–0.67]) were significantly associated with lower 2-year mortality than STR &lt;50% (11.7%). Successful STR was an independent predictor of 2-year mortality across the spectrum of clinical variables. After combining TIMI flow with STR, different 2-year mortality was observed in subgroups, with the lowest in successful STR and TIMI 3 flow, intermediate when either of these measures was reduced, and highest when both were abnormal.CONCLUSIONS: Post-PPCI STR is a robust long-term prognosticator for ST-segment–elevation myocardial infarction, whereas the integrated analysis of STR plus TIMI flow yields incremental prognostic information beyond either measure alone, support-ing it as a convenient and reliable surrogate end point for defining successful PPCI.</p

Role of ST-Segment Resolution Alone and in Combination With TIMI Flow After Primary Percutaneous Coronary Intervention for ST-Segment–Elevation Myocardial Infarction

BACKGROUND: To evaluate the role of ST-segment resolution (STR) alone and in combination with Thrombolysis in Myocardial Infarction (TIMI) flow in reperfusion evaluation after primary percutaneous coronary intervention (PPCI) for ST-segment– elevation myocardial infarction by investigating the long-term prognostic impact.METHODS AND RESULTS: From January 2013 through September 2014, we studied 5966 patients with ST-segment–elevation myocardial infarction enrolled in the CAMI (China Acute Myocardial Infarction) registry with available data of STR evaluated at 120 minutes after PPCI. Successful STR included STR ≥50% and complete STR (ST-segment back to the equipotential line). After PPCI, the TIMI flow was assessed. The primary outcome was 2-year all-cause mortality. STR &lt; 50%, STR ≥50%, and complete STR occurred in 20.6%, 64.3%, and 15.1% of patients, respectively. By multivariable analysis, STR ≥50% (5.6%; adjusted hazard ratio [HR], 0.45 [95% CI, 0.36–0.56]) and complete STR (5.1%; adjusted HR, 0.48 [95% CI, 0.34–0.67]) were significantly associated with lower 2-year mortality than STR &lt;50% (11.7%). Successful STR was an independent predictor of 2-year mortality across the spectrum of clinical variables. After combining TIMI flow with STR, different 2-year mortality was observed in subgroups, with the lowest in successful STR and TIMI 3 flow, intermediate when either of these measures was reduced, and highest when both were abnormal.CONCLUSIONS: Post-PPCI STR is a robust long-term prognosticator for ST-segment–elevation myocardial infarction, whereas the integrated analysis of STR plus TIMI flow yields incremental prognostic information beyond either measure alone, support-ing it as a convenient and reliable surrogate end point for defining successful PPCI.</p