new research paper on software testing

Artificial Intelligence is gradually changing the landscape of software engineering in general [5] and software testing in particular [6] both in research and industry as well. In the last two decades, AI has been found to have made a considerable impact on the way we are approach-ing software testing.

Software testing is a crucial component of software development. With the increasing complexity of software systems, traditional manual testing methods are becoming less feasible. Artificial Intelligence (AI) has emerged as a promising approach to software testing in recent years. This review paper aims to provide an in-depth understanding of the current state of software testing using AI. The ...

Software testing is the process of evaluating software applications to determine whether there are any defects, ensuring the quality of the software product. However, software testing is generally ...

Software testing (ST) and artificial intelligence (AI) are two research areas with a long and ripe history in computing. AI methodologies and techniques have been around for more than 50 years [] and, in the current century, with the advances in computational resources and the abundance of data, their potential has vastly increased.As a consequence, AI has been applied to fields as diverse as ...

We offer the following advice on how this data could inspire new research. An overview of the testing field: ... We based our analysis on publications retrieved using the term "software testing". This pool of papers included publications unrelated to software testing, e.g., the use of software to test hardware or as part of student ...

1 INTRODUCTION. Modern software development approaches, such as Agile, DevOps and continuous integration, have changed the way software is being developed [1, 2].Software products are released faster and more frequently than before—software release frequency improved from around 12 months in the last century to 3 weeks these days [].How to ensure development speed without sacrificing quality ...

Software Testing with Large Language Models: Survey, Landscape, and Vision ... from both the software testing and LLMs perspectives. The paper presents a detailed discussion of the software testing tasks for ... Since it is a new emerging field, there are many research opportunities, including exploring LLMs in an early stage of

Owing to these variations, numerous software testing challenges occur. This paper aims to recognize and to explain some of the biggest challenges that software testers face in dealing with AI/ML applications. For future research, this study has key implications. Each of the challenges outlined in this paper is ideal for further investigation ...

The paper provides a research agenda with elaborated directions for making progress toward advancing the state-of-the-art on testing of machine learning. Subjects: Software Engineering (cs.SE); Artificial Intelligence (cs.AI); Machine Learning (cs.LG) Cite as: arXiv:2205.00210 [cs.SE] (or arXiv:2205.00210v1 [cs.SE] for this version)

There have been rapid recent developments in automated software test design, repair and program improvement. Advances in artificial intelligence also have great potential impact to tackle software testing research problems. In this paper we highlight open research problems and challenges from an industrial perspective. This perspective draws on our experience at Meta Platforms, which has been ...

Despite the efforts of the software testing research community in the last several decades, various studies show that still many practitioners in the industry report challenges in their software testing tasks. Objective. To shed light on industry's challenges in software testing, we characterize and synthesize the challenges reported by ...

Also, ML has been used to evaluate test oracle construction and to predict the cost of testing-related activities. The results of this paper outline the ML algorithms that are most commonly used to automate software-testing activities, helping researchers to understand the current state of research concerning ML applied to software testing.

This paper provides a comprehensive review of various software testing models and optimization techniques available in the literature, emphasizing their performance analysis and related research ...

The paper also proposes some key contributions of AI in the future to the domain of software testing. Impact of AI on software Testing Activities AI techniques applied to software testing activities.

II. EXISTING TESTING METHODS. For the commencement of the Testing process, the first step is to generate test cases. The test cases are developed using various testing techniques, for the effective and accurate testing. The major testing techniques are Black box testing, White Box testing and Grey Box testing [8].

Binary Test-Suites Using Covering Arrays. Software testing is an essential activity to ensure the quality of software systems. Combinatorial testing is a method that facilitates the software testing process; it is based on an empirical evidence where almost all faults in a... more. Download. by Himer Avila-George. 2.

Ph.D. student Benjamin Mikek is the lead author of one of these papers, which looks to make SMT solvers faster and more efficient. Programmers use SMT solvers to analyze software to find possible program errors. Companies use these software analysis techniques to test software, such as Microsoft Word, for errors before it is available to users.

Both the AI and software testing researchers and Practitioners must lead the innovations to address their integrating challenges. AI and Machine Learning (ML) have the potential to advance the capabilities to test the software intensely. The objective of the paper is to review the state-of-the-art of applying AI in software testing briefly.

According to IBM, AI-based testing can reduce software defects by up to 30%. AI can further anticipate the specific functionality that might crash under heavy load by analyzing millions of lines ...

This paper provides technical details for Apple's On-Device and Server Foundation Models, introduced on June 10, 2024, in this post. Related readings and updates. ... Our research in machine learning breaks new ground every day. Work with us. Machine Learning Research; Research;

PDF | On Jan 3, 2020, Arun Kumar Arumugam published Software Testing Techniques New Trends | Find, read and cite all the research you need on ResearchGate

Read content policy (opens in a new window) Phased deployment based on learning Learning from real-world use is an important part of developing and deploying AI responsibly. We began by previewing DALL·E 2 to a limited number of trusted users. ... Research Advancements. Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen.

Realistically and consistently synthesize new videos. Either by applying the composition and style of an image or text prompt to the structure of a source video (Video to Video). Or, using nothing but words (Text to Video). ... Runway Research is dedicated to building the multimodal AI systems that will enable new forms of creativity. Gen-1 ...

Artificial Intelligence (AI) is making a significant impact in multiple areas like medical, military, industrial, domestic, law, arts as AI is capable to perform several roles such as managing smart factories, driving autonomous vehicles, creating accurate weather forecasts, detecting cancer and personal assistants, etc. Software testing is the process of putting the software to test for some ...

OpenAI is testing an A.I.-powered search engine that can access information from across the internet in real time. The prominent A.I. start-up revealed the new prototype, SearchGPT, in a blog post ...

Luna Lu, at left, and students in her lab made the discoveries and conducted the experiments that have led to the development of a promising new concrete strength testing method and commercial product. Cihang Huang, at right, a PhD student in the Lyles School of Civil and Construction Engineering, is part of Lu's research group.

Abstract: From the early days of computer systems to the present, software testing has been considered as a crucial process that directly affects the quality and reliability of software-oriented products and services. Accordingly, there is a huge amount of literature regarding the improvement of software testing approaches. However, there are limited reviews that show the whole picture of the ...

Using data on 57 million children, we show that intergenerational mobility changed rapidly by race and class in recent decades. For white children in the U.S. born between 1978 and 1992, earnings increased for children from high-income families but decreased for children from low-income families, increasing earnings gaps by parental income ("class") by 30%.

Explore the latest full-text research PDFs, articles, conference papers, preprints and more on SOFTWARE QUALITY ASSURANCE. Find methods information, sources, references or conduct a literature ...

SAN FRANCISCO, July 29 (Reuters) - Apple , opens new tab relied on chips designed by Google rather than industry leader Nvidia to build two key components of its artificial intelligence software ...