4,951 papers · page 27 of 248
To support high reliability and availability, modern cloud systems are designed to be resilient to node crashes and reboots. That is, a cloud system should gracefully recover from node crashes/reboots and continue to function. However, node crashes/reboots that occur under specia…
Previous studies have demonstrated that neural code comprehension models are vulnerable to identifier naming. By renaming as few as one identifier in the source code, the models would output completely irrelevant results, indicating that identifiers can be misleading for model pr…
Previous research on code intelligence usually trains a deep learning model on a fixed dataset in an offline manner. However, in real-world scenarios, new code repositories emerge incessantly, and the carried new knowledge is beneficial for providing up-to-date code intelligence …
Interpreting and debugging machine learning models is necessary to ensure the robustness of the machine learning models. Explaining mispredictions can help significantly in doing so. While recent works on misprediction explanation have proven promising in generating interpretable…
As most smart contracts have a financial nature and handle valuable assets, smart contract developers use access control to protect assets managed by smart contracts from being misused by malicious or unauthorized people. Unfortunately, programming languages used for writing smar…
Software bots fulfill an important role in collective software development, and their adoption by developers promises increased productivity. Past research has identified that bots that communicate too often can irritate developers, which affects the utility of the bot. However, …
In Federated Learning (FL), clients independently train local models and share them with a central aggregator to build a global model. Impermissibility to access clients' data and collaborative training make FL appealing for applications with data-privacy concerns, such as medica…
Machine Learning (ML) software has been widely adopted in modern society, with reported fairness implications for minority groups based on race, sex, age, etc. Many recent works have proposed methods to measure and mitigate algorithmic bias in ML models. The existing approaches f…
Block-based programming languages like Scratch are increasingly popular for programming education and end-user programming. Recent program analyses build on the insight that source code can be modelled using techniques from natural language processing. Many of the regularities of…
Due to the great advance in machine learning (ML) techniques, numerous ML models are expanding their application domains in recent years. To adapt for resource-constrained platforms such as mobile and Internet of Things (IoT) devices, pre-trained models are often processed to enh…
Company engagement in open source (OSS) is now the new norm. From large technology companies to startups, companies are participating in the OSS ecosystem by open-sourcing their technology, sponsoring projects through funding or paid developer time. However, our understanding of …
Binding calls of embedded scripting engines introduce a serious attack surface in PDF readers. To effectively test binding calls, the knowledge of parameter types is necessary. Unfortunately, due to the absence or incompleteness of documentation and the lack of sufficient samples…
Termination is a fundamental liveness property for program verification. In this paper, we revisit the problem of non-termination analysis and propose the first data-driven learning algorithm for synthesizing recurrent sets, where the non-terminating samples are effectively specu…
Deep Neural Networks (DNNs) have been widely used to perform real-world tasks in cyber-physical systems such as Autonomous Driving Systems (ADS). Ensuring the correct behavior of such DNN-Enabled Systems (DES) is a crucial topic. Online testing is one of the promising modes for t…
Concurrent programs suffer from data races. To prevent data races, programmers use locks. However, programs can eliminate data races only when they acquire and release correct locks at correct timing. The lock API of C, in which people have developed a large portion of legacy sys…
Structural code coverage is a popular test adequacy metric that measures the percentage of program structure (e.g., statement, branch, decision) executed by a test suite. While structural coverage has several benefits, previous studies suggested that code coverage is not a good i…
Deep learning (DL) plays a more and more important role in our daily life due to its competitive performance in industrial application domains. As the core of DL-enabled systems, deep neural networks (DNNs) need to be carefully evaluated to ensure the produced models match the ex…
Vehicles controlled by autonomous driving software (ADS) are expected to bring many social and economic benefits, but at the current stage not being broadly used due to concerns with regard to their safety. Virtual tests, where autonomous vehicles are tested in software simulatio…
Modern software development extensively depends on existing libraries written by other developer teams from the same or a different organization. When a developer executes the software, the execution trace may go across the boundaries of multiple software products and create cros…
Bug reports are vital for software maintenance that allow the developers being informed of the problems encountered in the software. Before bug fixing, developers need to reproduce the bugs which is an extremely time-consuming and tedious task, and it is highly expected to automa…