INTERNETWARE

Neural code intelligence models are cutting-edge automated code understanding technologies that have achieved remarkable performance in various software engineering tasks. However, the lack of deep learning models’ interpretability hinders the ...

API migration is an essential step for code migration between libraries or programming languages, and it is a challenging task as it requires detailed comprehension of both source and target APIs. The existing work either recommends mapped API names ...

Recent advances in deep learning have significantly improved the understanding of source code by leveraging large amounts of open-source software data. Thanks to the larger amount of data, code representation models trained with multilingual datasets ...

API recommendation has been widely used to enhance developers’ efficiency in software development. However, existing API recommendation methods for dynamic languages such as Python usually suffer from the limitations of incorrect type inference and lack ...

Recent years have seen a growing interest in deep learning-based approaches to localize faults in software. However, existing methods have not reached a satisfying level of accuracy. The main reason is that the feature extraction of faulty code ...

The calling relationship between projects becomes complicated as the number of open-source projects increases. Different issues across projects can also be related, referred to as cross-project correlated issues (CPCIs), and bring new challenges for ...

Previous research have utilized public software defect datasets such as NASA, RELINK, and SOFTLAB, which only contain class label information. Almost all Effort-Aware Defect Prediction (EADP) studies are carried out around these datasets. However, EADP ...

Smart contracts are one of the most successful applications of blockchain technology. In order to guarantee the security of smart contracts, researchers have successively introduced various testing methodologies, including static analysis, symbolic ...

The emergence of build automation tools with dependency management features has significantly impacted software development. However, in the configuration process, improper settings of some configuration items, such as the dependency scope setting, may ...

Open-source software (OSS) projects have become a cornerstone of the software ecosystem, offering numerous benefits to developers and end-users alike. However, ensuring the long-term sustainability and success of OSS projects is challenging, requiring ...

Millions of apps in markets have made it difficult for mobile users to find fancy and high quality apps. Mobile app markets have deployed mechanisms to recommend apps to users. Apple usually features apps in the iOS App Store, and mobile users could ...

The widespread adoption of deep learning (DL) has made it critical to ensure its reliability. Mutation testing has been employed in DL testing to assess test data quality, but it can be costly of a large number of generated mutants. Cost reduction can ...

The Ubiquitous Operating System(UOS) is a new type of operating system in response to the new patterns and scenarios of future human-cyber-physical ternary ubiquitous computing. Compared with traditional operating systems, one of the fundamental ...

Internet of Things (IoT) software is used to control the distributed hardware of the underlying network and provide a reliable operating platform for various services. In production system, diversity IoT software provides multiple services, flows of ...

A software exploit is a sequence of commands that exploits software vulnerabilities or security flaws, written either by security researchers as a Proof-Of-Concept (POC) threat or by malicious attackers for use in their operations. Writing exploits is ...

Buffer overflow vulnerabilities are prevalent in software applications, and their automatic detection and exploitation are of great significance. Modern operating systems implement security mitigation to prevent the exploitation of these ...

Software vulnerabilities can cause severe security threats to cyberspace, and it is of significant importance to conduct automated vulnerability detection research. Considering that the source code contains rich syntax and semantic information, plenty ...

The detection of software vulnerability is an important and challenging problem. Existing studies have shown that deep learning-based approaches can significantly improve the performance of vulnerability detection due to their powerful capabilities of ...

Object detection models have been widely deployed in military and life-related intelligent software systems. However, along with the outstanding success of object detection, it may exhibit abnormal behavior and lead to severe accidents and losses. ...

As deep learning systems have been widely deployed in many safety-critical scenarios, their quality and reliability have raised growing concerns. Assuring the quality and evaluating the accuracy of deep learning models could be challenging because, ...

With the widespread adoption of the JavaScript language, JavaScript engines have become a primary target for attackers, leading to numerous security threats. To expose potential security vulnerabilities and bugs in JavaScript engines, various fuzzing ...

As production code evolves, test code can quickly become outdated. When test code is outdated, it may fail to capture errors in the programs under test and can lead to serious software bugs that result in significant losses for both developers and ...

Code generation aims to automatically generate the source code based on given natural language (NL) descriptions, which is of great significance for automated software development. Some code generation models follow a language model-based paradigm (...

Although efficiency is one of the core metrics in programming, recent large-scale language models often face the issue of “inefficient code” generation, which struggles to meet the real-time requirements of algorithms. However, there is relatively ...

Based on developer needs and usage scenarios, API (Application Programming Interface) recommendation is the process of assisting developers in finding the required API among numerous candidate APIs. Previous studies mainly modeled API recommendation as ...

Code search has been a critical software development activity in facilitating developers to retrieve a proper code snippet from open-source repositories given a user intent. In recent years, large-scale pre-trained models have shown impressive ...

Recent research introduces deep learning algorithms such as recurrent neural networks (RNNs) to predict the next activity, one of the most challenging tasks in predictive business process monitoring. However, the RNN-based models use only the last ...

Energy-efficiency now severely restricts the sustainable operation and development of big data services. In this paper, we propose a bi-objective configuration parameters auto-tuning method EFTuner towards energy-efficient big data processing. ...

Internet-scale distributed systems often rely on replication to achieve fault-tolerance and load distribution. To provide low latency and high availability, the systems are often required to accept updates on one replica immediately and then propagate ...

As online coding technology advances, various related products are emerging, but we observe that there are not many examples of introducing online coding into the field of theorem proving. We introduce Isabelle/Cloud, an online coding platform and user ...