3,458 papers · page 65 of 173
A key challenge in automatic Web testing is the generation of syntactically and semantically valid input values that can exercise the many functionalities that impose constraints on the validity of the inputs. Existing test case generation techniques either rely on manually curat…
Library migration is a challenging problem, where most existing approaches rely on prior knowledge. This can be, for example, information derived from changelogs or statistical models of API usage.
Formal specifications in Alloy are organized around user-defined data domains, associated with signatures, with almost no support for built-in datatypes. This minimality in the built-in datatypes provided by the language is one of its main features, as it contributes to the autom…
Approaches for automatic crash reproduction aim to generate test cases that reproduce crashes starting from the crash stack traces. These tests help developers during their debugging practices. One of the most promising techniques in this research field leverages search-based sof…
Writing a test case reproducing a reported software crash is a common practice to identify the root cause of an anomaly in the software under test. However, this task is usually labor-intensive and time-taking. Hence, evolutionary intelligence approaches have been successfully ap…
The design and implementation of artificial intelligence driven software that keeps user data private is a complex yet necessary requirement in the current times. Developers must consider several ethical and legal challenges while developing services which relay massive amount of…
Machine Learning models from other fields, like Computational Linguistics, have been transplanted to Software Engineering tasks, often quite successfully. Yet a transplanted model's initial success at a given task does not necessarily mean it is well-suited for the task. In this …
Regression testing is widely recognized as an important but time-consuming process. To alleviate this cost issue, test selection, reduction, and prioritization have been widely studied, and they share the commonality that they improve regression testing by optimizing the executio…
Neural networks are becoming a popular tool for solving many real-world problems such as object recognition and machine translation, thanks to its exceptional performance as an end-to-end solution. However, neural networks are complex black-box models, which hinders humans from i…
Understanding the influence of configuration options on performance is key for finding optimal system configurations, system understanding, and performance debugging. In prior research, a number of performance-influence modeling approaches have been proposed, which model a config…
State-of-the-art deep learning (DL) systems are vulnerable to adversarial examples, which hinders their potential adoption in safety-and security-critical scenarios. While some recent progress has been made in analyzing the robustness of feed-forward neural networks, the robustne…
Strings play many roles in programming because they often contain complex and semantically rich information. For example, programmers use strings to filter inputs via regular expression matching, to express the names of program elements accessed through some form of reflection, t…
Randomised compiler testing techniques require a means of generating programs that are free from undefined behaviour (UB) in order to reliably reveal miscompilation bugs. Existing program generators such asCsmithheavily restrict the form of generated programs inorder to achieve U…
Mobile apps interact with their environment extensively, and these interactions can complicate testing activities because test cases may need a complete environment to be executed. Interactions with the environment can also introduce test flakiness, for instance when the environm…
Because creating and maintaining an in-house test lab is expensive and time-consuming, companies and app developers often use device clouds to test their apps. Because quality-assurance activities depend on such device clouds, it is important to understand possible issues related…
The data race problem is common in the interrupt-driven program, and it is difficult to find as a result of complicated interrupt interleaving. Static analysis is a mainstream technology to detect those problems, however, the synchronization mechanism of interrupt is hard to be p…
Client-specific equivalence checking (CSEC) is a technique proposed previously to perform impact analysis of changes to downstream components (libraries) from the perspective of an unchanged system (client). Existing analysis techniques, whether general (regression verification, …
This paper presents Solar, a system for automatic synthesis of adversarial contracts that exploit vulnerabilities in a victim smart contract. To make the synthesis tractable, we introduce a query language as well as summary-based symbolic evaluation, which significantly reduces t…
Over the last few years, there has been substantial research on automated analysis, testing, and debugging of Ethereum smart contracts. However, it is not trivial to compare and reproduce that research. To address this, we present SmartBugs, an extensible and easy-to-use executio…
Background: The detection and extraction of causality from natural language sentences have shown great potential in various fields of application. The field of requirements engineering is eligible for multiple reasons: (1) requirements artifacts are primarily written in natural l…