相关论文: DroidWalker: Generating Reproducible Test Cases vi…

Workflows are critical for scientific discovery. However, the sophistication, heterogeneity, and scale of workflows make building, testing, and optimizing them increasingly challenging. Furthermore, their complexity and heterogeneity make…

Mobile apps increasingly rely on real-time sensor and system data to adapt their behavior to user context. While emulators and instrumented builds offer partial solutions, they often fail to support reproducible testing of context-sensitive…

Cryptographic (crypto) algorithms are the essential ingredients of all secure systems: crypto hash functions and encryption algorithms, for example, can guarantee properties such as integrity and confidentiality. Developers, however, can…

In training their newly-developed malware detection methods, researchers rely on threshold-based labeling strategies that interpret the scan reports provided by online platforms, such as VirusTotal. The dynamicity of this platform renders…

With the recent advances of open-domain story generation, the lack of reliable automatic evaluation metrics becomes an increasingly imperative issue that hinders the fast development of story generation. According to conducted researches in…

Intelligent Apps (iApps), equipped with in-App deep learning (DL) models, are emerging to offer stable DL inference services. However, App marketplaces have trouble auto testing iApps because the in-App model is black-box and couples with…

With the growing capabilities of autonomous vehicles, there is a higher demand for sophisticated and pragmatic quality assurance approaches for machine learning-enabled systems in the automotive AI context. The use of simulation-based…

Large language models have opened up a world of possibilities for various NLP tasks, sparking optimism for the future. Despite their potential, LLMs have yet to be widely used as agents on real mobile devices. The main challenge is the need…

As the popularity of Smart Televisions (TVs) and interactive Smart TV applications (apps) has recently grown, the usability of these apps has become an important quality characteristic. Previous studies examined Smart TV apps from a…

The state space of Android apps is huge and its thorough exploration during testing remains a major challenge. In fact, the best exploration strategy is highly dependent on the features of the app under test. Reinforcement Learning (RL) is…

Resource leak bugs in Android apps are pervasive and can cause serious performance degradation and system crashes. In recent years, several resource leak detection techniques have been proposed to assist Android developers in correctly…

Games are usually created incrementally, requiring repeated testing of the same scenarios, which is a tedious and error-prone task for game developers. Therefore, we aim to alleviate this game testing process by encapsulating it into a game…

Dealing with the evolution of operating systems is challenging for developers of mobile apps, who have to deal with frequent upgrades that often include backward incompatible changes of the underlying API framework. As a consequence of…

There have been many studies on automated test generation for mobile Graphical User Interface (GUI) applications. These studies successfully demonstrate how to detect fatal exceptions and achieve high code and activity coverage with fully…

In the mobile development process, creating the user interface (UI) is highly resource intensive. Consequently, numerous studies have focused on automating UI development, such as generating UI from screenshots or design specifications.…

Graphical User Interfaces (GUIs) are the primary means by which users interact with mobile applications, making them crucial to both app functionality and user experience. However, a major challenge in automated testing is the frequent…

The rise of Virtual Reality (VR) has provided developers with an unprecedented platform for creating games and applications (apps) that require distinct inputs, different from those of conventional devices like smartphones. The Meta Quest…

Due to the complexity of robotics, the reproducibility of results and experiments is one of the fundamental problems in robotics research. While the problem has been identified by the community, the approaches that address the problem…

A common concern in experimental research is the auditability and reproducibility of experiments. Experiments are usually designed, provisioned, managed, and analyzed by diverse teams of specialists (e.g., researchers, technicians and…

As reinforcement learning (RL) achieves more success in solving complex tasks, more care is needed to ensure that RL research is reproducible and that algorithms herein can be compared easily and fairly with minimal bias. RL results are,…