Abstract: The evolution of software quality models (SQMs) reflects the dynamic of the development of information technologies and systems. For new specialised information technologies, it is necessary ...

Abstract: Software evolution and bad smells have been widely studied over past two decades, occurring at architecture, design, implementation, and requirement levels. Design smells, which result from ...

Quantum computing represents a potential breakthrough technology that could far surpass the technical limitations of modern-day computing systems for some tasks. However, putting together practical, ...

The Charlottesville Police Department recently ended a pilot program that involved the use of artificial intelligence software and license plate reading cameras to help solve crimes in Charlottesville ...

Dane County Executive Melissa Agard announces the launch of the ATTA program at the City-County Building. (Photo: Dane County Executive's office) Dane County has launched the Assessment, Treatment, ...

Cars are returning to dealerships in record numbers to have software fixes injected into vehicles given a sixth-straight year of a record number of software recalls and little momentum on over-the-air ...

After jumping from the bustling streets of Chicago to the humble countryside in North Carolina, new professor Dan Elliott is ready to make his mark at the University of Louisville’s Hite Institute of ...

Grants will now be distributed through a wishlist and requests for proposals, aligning funding with the Ethereum ecosystem’s goals. The Ethereum Foundation (EF) has overhauled its grants program, ...

The States Leading States initiative — a Harvard Graduate School of Education program that aims to identify effective schooling policies by analyzing state education programs — announced its first ...

The Harrelson Center's housing navigation program aims to prevent homelessness in New Hanover County. The program supports renters and homeowners who are at risk of losing their housing. Of the first ...

A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.