3,458 papers · page 58 of 173
Robustness is a key concern for Rust library development because Rust promises no risks of undefined behaviors if developers use safe APIs only. Fuzzing is a practical approach for examining the robustness of programs. However, existing fuzzing tools are not directly applicable t…
Part-of-Speech (POS) tagging for sentences is a basic and widely-used Natural Language Processing (NLP) technique. People rely heavily on it to predict POS tags that serve as the base for many advanced NLP tasks, such as sentiment analysis, word sense disambiguation, and informat…
Dynamic programming languages have been embracing gradual typing, which supports optional type annotations in source code. Type-annotating a complex and long-lasting codebase is indeed a gradual and expensive process, where two issues have troubled developers. First, there is few…
This research explores the possibility of a new anti-analysis technique, carefully designed to attack weaknesses of the existing program analysis approaches. It encodes a program code snippet to hide, and its decoding process is implemented by a sophisticated state machine that p…
Pre-trained models of code built on the transformer architecture have performed well on software engineering (SE) tasks such as predictive code generation, code summarization, among others. However, whether the vector representations from these pre-trained models comprehensively …
Programmers often use Q&A sites (e.g., Stack Overflow) to understand a root cause of program bugs. Runtime exceptions is one of such important class of bugs that is actively discussed on Stack Overflow. However, it may be difficult for beginner programmers to come up with appropr…
Many program verification tools can be customized via run-time configuration options that trade off performance, precision, and soundness. However, in practice, users often run tools under their default configurations, because understanding these tradeoffs requires significant ex…
Software containers, such as Docker, are recently considered as the mainstream technology of providing reusable software artifacts. Developers can easily build and deploy their applications based on the large number of reusable Docker images that are publicly available. Thus, a c…
In agile software development, proper team structures and effort estimates are crucial to ensure the on-time delivery of software projects. Delivery performance can vary due to the influence of changes in teams, resulting in team dynamics that remain largely unexplored. In this p…
This paper presents Arvada, an algorithm for learning context-free grammars from a set of positive examples and a Boolean-valued oracle. Arvada learns a context-free grammar by building parse trees from the positive examples. Starting from initially flat trees, Arvada builds stru…
Inspection of code changes is a time-consuming task that constitutes a big part of everyday work of software engineers. Existing IDEs provide little information about the semantics of code changes within the file editor view. Therefore developers have to track changes across mult…
Effective locating and fixing defects requires detailed defect reports. Unlike traditional software systems, machine learning applications are subject defects caused from changes in the input data streams (concept drift) and assumptions encoded into models. Without appropriate tr…
It is increasingly suggested to identify Software Vulnerabilities (SVs) in code commits to give early warnings about potential security risks. However, there is a lack of effort to assess vulnerability-contributing commits right after they are detected to provide timely informati…
Software systems often record important runtime information in system logs for troubleshooting purposes. There have been many studies that use log data to construct machine learning models for detecting system anomalies. Through our empirical study, we find that existing log-base…
Signal temporal logic (STL) is widely used to specify and analyze properties of cyber-physical systems with continuous behaviors. However, STL model checking is still quite limited, as existing STL model checking methods are either incomplete or very inefficient. This paper prese…
Deep learning-based techniques have been widely applied to program analysis tasks, in fields such as type inference, fault localization, and code summarization. Hitherto deep learning-based software engineering systems rely thoroughly on supervised learning approaches, which requ…
When users deploy or invoke smart contracts on Ethereum, a fee is charged for avoiding resource abuse. Metered in gas, the fee is the product of the amount of gas used and the gas price. The more gas used indicates a higher transaction fee. In my doctoral research, we aim to inve…
Existing studies show that code summaries help developers understand and maintain source code. Unfortunately, these summaries are often missing or outdated in software projects. Code summarization aims to generate natural language descriptions automatically for source code. Accor…
Markdown compilers are widely used for translating plain Markdown text into formatted text, yet they suffer from performance bugs that cause performance degradation and resource exhaustion. Currently, there is little knowledge and understanding about these performance bugs in the…
Recent years have seen a rapid development of machine learning based multi-module unmanned aerial vehicle (UAV) systems. To address the oracle problem in autonomous systems, numerous studies have been conducted to use metamorphic testing to automatically generate test scenes for …