Slow and insufficient definition of requirements, time-consuming coding and error-prone bug detection are just some of the issues that teams face in the software development life cycle (SDLC).

In today's enterprise landscape, software development often resembles a game of telephone. Business users articulate needs, and—after those needs go through layers of marketing, product and ...

Considering the scaling history and trajectory of generative AI models (specifically large language models, or LLMs) specialized for coding, the software development life cycle (SDLC) is ripe for ...

Code generation and copilots are just the beginning of new AI-enabled ways to develop, test, deploy, and maintain software. Coding in the 1990s usually meant selecting an editor, checking code into ...

A systematic approach that views the clinical research department as an integral part of the development team can enhance the likelihood of success in the creation of new products. Nancy J. Stark Many ...