26,098 papers · page 238 of 1,305
Creating synthetic behaviors of vehicles in simulation applications has always been challenging from a development standpoint. First, it is a real challenge to create a credible and realistic simulation while achieving the required runtime efficiency. Second, the effort required …
[Background:] Automated Intelligent Toolchains, which are a composition of different tools that use AI or static analysis, are widely used in software engineering to deploy automated program repair techniques, or in software security to identify vulnerabilities. [Overall Research…
Sustainable software engineering has received a lot of attention in recent times, as we witness an ever-growing slice of energy use, for example, at data centers, as software systems utilize the underlying infrastructure. Characterizing servers for their energy use accurately wit…
More apps are published every day and the functionality of each app increases steadily as well. Consequently app analyses are often overwhelmed when confronted with up-to-date, real-world apps. One of the biggest issues originates from the scalability of analyses with respect to …
During code reviews, software developers often raise security concerns if they find any. Ignoring such concerns can bring a severe impact on the performance of a software product. This risk can be reduced if we can automatically identify such code reviews that trigger security co…
In the context of software development, managing and organizing agile boards of multi-disciplinary teams distributed around the world is a great challenge, especially regarding the process of assigning tickets to the correct team roles. Incorrectly assigned tickets can result in …
Presence monitoring or intrusion detection in a location/area are examples of decision-support applications. Decision-support applications are applications where monitoring is used to collect (heterogeneous) data and create situational awareness, which further requires decisions …
Software testing is a process of evaluating and verifying whether a software product still works as expected, and it is repetitive, laborious, and time-consuming. To address this problem, automation tools have been developed to automate testing activities and enhance quality and …
The process of creating test cases from requirements written in natural language (NL) requires intensive human efforts and can be tedious, repetitive, and error-prone. Thus, many studies have attempted to automate that process by utilizing Natural Language Processing (NLP) approa…
Fuzz testing (“fuzzing”) is a widely-used and effective dynamic technique to discover crashes and security vulnerabilities in software, supported by numerous tools, which keep improving in terms of their detection capabilities and speed of execution. In this paper, we report our …
Artificial diversification of a software program can be a versatile tool in a wide range of software engineering and security scenarios. For example, randomizing implementation aspects can increase the costs for attackers as it prevents them from benefiting of precise knowledge o…
Despite great success in many applications, deep neural networks are not always robust in practice. For instance, a convolutional neuron network (CNN) model for classification tasks often performs unsatisfactorily in classifying some particular classes of objects. In this work, w…
Optical character recognition (OCR) algorithms often run slow. They may take several seconds to recognize the texts on a GUI screen, which makes OCR-based widget localization in test automation unfriendly for use, especially on GPU-free computers. This paper first concludes a com…
Virtual Reality (VR) technology has been utilized in other fields besides gaming, such as education, training, arts, shopping, and e-commerce. However, the technical support of VR software is not growing as fast as its market size, especially for testing. Because of the immersive…
As software systems continue to grow in complexity and scale, deploying and delivering them becomes increasingly difficult. In this work, we develop DeployQA, a novel QA bot that automatically answers software deployment questions over user manuals and Stack Overflow posts. Deplo…
Quality assurance is of great importance for deep learning (DL) systems, especially when they are applied in safety-critical applications. While quality issues of native DL applications have been extensively analyzed, the issues of JavaScript-based DL applications have never been…
While the emerging Augmented Reality (AR) technique allows a lot of new application opportunities, from education and communication to gaming, current augmented apps often have complaints about their usability and/or user experience due to placement errors of virtual objects. The…
Communication nondeterminism is one of the main reasons for the intractability of verification of message passing concurrency. In many practical message passing programs, the non-deterministic communication structure is symmetric and decomposed into epochs to obtain efficiency. T…
Infrastructure-as-Code (IaC) is a technology that enables the management and distribution of infrastructure through code instead of manual processes. In 2020, Palo Alto Network’s Unit 42 announced the discovery of over 199K vulnerable IaC templates through their “Cloud Threat” Re…
Machine learning (ML) systems based on deep neural networks are more present than ever in software solutions for numerous industries. Their inner workings relying on models learning with data are as helpful as they are mysterious for non-expert people. There is an increasing need…