相关论文: AI and Agile Software Development: From Frustratio…

This paper identifies and tackles the challenges of the requirements engineering discipline when applied to development of AI-based complex systems. Due to their complex behaviour, there is an immanent need for a tailored development…

Requirement Engineering (RE) is the foundation of successful software development. In RE, the goal is to ensure that implemented systems satisfy stakeholder needs through rigorous requirements elicitation, validation, and evaluation…

The lack of interpretability is a major barrier that limits the practical usage of AI models. Several eXplainable AI (XAI) techniques (e.g., SHAP, LIME) have been employed to interpret these models' performance. However, users often face…

Agile Development is used for many problems, often with different priorities and challenges. However, generalized engineering methodologies often overlook the particularities of a project. To solve this problem, we have looked at ways…

A new transformation is underway in software engineering, driven by the rapid adoption of generative AI in development workflows. Similar to how version control systems once automated manual coordination, AI tools are now beginning to…

The software engineering community recently has witnessed widespread deployment of AI programming assistants, such as GitHub Copilot. However, in practice, developers do not accept AI programming assistants' initial suggestions at a high…

To improve the Information Technology (I.T.) graduate skill set, students need to be immersed in as realistic a software development environment as possible. In continuing our work on integrating Agile Methodology into the Capstone Program…

In the software industry, artificial intelligence (AI) has been utilized more and more in software development activities. In some activities, such as coding, AI has already been an everyday tool, but in software testing activities AI it…

The importance of continuously incorporating customer feedback in the software development process is well established and firmly grounded in concepts such as agile and DevOps. In large-scale organizations such as Dell Technologies however,…

Under the EU AI Act, translating AI governance requirements into software development practice remains challenging. While AI governance frameworks exist at industry and organizational levels, empirical evidence of team-level implementation…

While organizations want to develop software products with reduced cost and flexible scope, stories about the applicability of agile practices to improve project development and performance in the software industry are scarce and focused on…

In the last decade, several studies have explored automated techniques to estimate the effort of agile software development. We perform a close replication and extension of a seminal work proposing the use of Deep Learning for Agile Effort…

Software developers and project managers are struggling to assess the appropriateness of agile processes to their development environments. This paper identifies limitations that apply to many of the published agile processes in terms of…

Agile software development is nowadays a widely adopted practise in both open-source and industrial software projects. Agile teams typically heavily rely on issue management tools to document new issues and keep track of outstanding ones,…

Although agile software development methods have caught the attention of software engineers and researchers worldwide, scientific research still remains quite scarce. The aim of this study is to order and make sense of the different agile…

Computer-Aided Engineering (CAE) enables simulation experts to optimize complex models, but faces challenges in user experience (UX) that limit efficiency and accessibility. While artificial intelligence (AI) has demonstrated potential to…

Developing and certifying safe - or so-called trustworthy - AI has become an increasingly salient issue, especially in light of upcoming regulation such as the EU AI Act. In this context, the black-box nature of machine learning models…

The past decade has seen significant progress in artificial intelligence (AI), which has resulted in algorithms being adopted for resolving a variety of problems. However, this success has been met by increasing model complexity and…

The ultimate goal of artificial intelligence (AI) is to achieve Artificial General Intelligence (AGI). Embodied Artificial Intelligence (EAI), which involves intelligent systems with physical presence and real-time interaction with the…

After introducing agile approach in 2001, several agile methods were founded over the last decade. Agile values such as customer collaboration, embracing changes, iteration and frequent delivery, continuous integration, etc. motivate all…