Code refactoring is an essential part of software development, because it reduces technical debt, enhances long-term code sustainability, and enables the implementation of functionality that might have been incompatible with an original design. IDEs ...

This special issue about Generative AI (GAI) for software engineering refers to applying generative models and algorithms in software development, testing, maintenance and evolution. This special issue features five articles where you will see some ...

In Episode 626 of “Software Engineering Radio,” Ipek Ozkaya, principal researcher and technical director of the Engineering Intelligent Software Systems Group at the Software Engineering Institute, Carnegie Mellon, discusses generative AI for software ...

An ethical approach to AI need not be revolutionary or exceptional. We argue that it is the ethical duty of software professionals to rally against AI over-hype. As shown here, this is not hard to do. If we apply just simple empirical methods, we can ...

Trust is central to how developers engage with AI. In this article, we discuss what we learned from developers about their level of trust in AI powered developer tooling, and how we translated those findings into product design recommendations to support ...

Requirements engineering plays a crucial role in understanding stakeholder needs, ensuring quality attributes, and facilitating effective communication in various domains. Software testing helps ensure that software products meet requirements and quality ...

In this final issue of the year, we mark a milestone: IEEE Software’s 40th anniversary—a ruby jubilee! While this column still awaits the silver achievement badge (25 years)—Suzanne Robertsson founded it in the early millennium—I’m pleased to present a ...

The emergence of quantum computing proposes a revolutionary paradigm that can radically transform numerous scientific and industrial application domains. However, realizing this promise in industrial applications is far from being practical today. In this ...

Presents a panel discussion on the topic of Observability for Large Language Models.

Developers benefit from enhanced productivity with GAI. Yet, often they question how to approach GAI development and how to integrate GAI to their systems. This article provides guidance for developing GAI software and developing software with GAI. ...

From Fagan Inspections to cleanroom practices, agile code reviews, mob programming, and failing fast. This editorial provides a personal reflection of how the practice of code reviews has changed over the decades.

Understanding and effectively measuring developer goals is critical for enhancing developer experience and productivity. By focusing on durable, consistent, relatable, sensical, and observable goals we create a more robust view into our developers’ days. ...

Generative LLMs, such as GPT, have the potential to revolutionize Requirements Engineering (RE) by automating tasks in new ways. This column explores the novelties and introduces the importance of precise prompts for effective interactions. Human ...

The benefits of AI come at considerable energy cost to the environment. What is the role of software engineering in mitigating that cost? To find out, IEEE Software spoke to Dr. Federica Sarro, a Professor of Software Engineering at University College, ...

Engineering AI Software systems is starting to evolve from the pure development of machine learning (ML) models to a more structured discipline that treats ML components as part of much larger software systems. As such, more structured principles are ...

In this study, we investigate what has been discussed about generative AI in the code review context by performing a gray literature review. We analyzed 42 documents and found insights from practice and proposals of solutions using generative AI models.

High quality data is essential for designing effective software test suites. We propose three original methods for using large language models to generate representative test data, which fit to the domain of the program under test and are culturally ...

We present a validated framework for the evaluation and comparison of three main third-generation blockchain categories, based on the three main nonfunctional aspects that discriminate their use for the design and orchestration of complex blockchain-...

This article presents a novel framework that combines the hazard and operability analysis with generative AI to support a safety expert in identifying safety hazards, their causes and consequences, and to propose mitigation strategies.

To address AI architecture design challenges, we present an architecture evolution of AI systems in the era of foundation models, transitioning from “foundation-model-as-a-connector” to “foundation-model-as-a-monolithic architecture.” We then identify key ...