Ingrid Sundbø

2papers

2 Papers

SENov 7, 2020
Software engineering for artificial intelligence and machine learning software: A systematic literature review

Elizamary Nascimento, Anh Nguyen-Duc, Ingrid Sundbø et al.

Artificial Intelligence (AI) or Machine Learning (ML) systems have been widely adopted as value propositions by companies in all industries in order to create or extend the services and products they offer. However, developing AI/ML systems has presented several engineering problems that are different from those that arise in, non-AI/ML software development. This study aims to investigate how software engineering (SE) has been applied in the development of AI/ML systems and identify challenges and practices that are applicable and determine whether they meet the needs of professionals. Also, we assessed whether these SE practices apply to different contexts, and in which areas they may be applicable. We conducted a systematic review of literature from 1990 to 2019 to (i) understand and summarize the current state of the art in this field and (ii) analyze its limitations and open challenges that will drive future research. Our results show these systems are developed on a lab context or a large company and followed a research-driven development process. The main challenges faced by professionals are in areas of testing, AI software quality, and data management. The contribution types of most of the proposed SE practices are guidelines, lessons learned, and tools.

CYAug 14, 2018
Evaluation of team dynamic in Norwegian projects for IT students

Salah Uddin Ahmed, Ingrid Sundbø, Jon Kvisli et al.

The need for teaching realistic software development in project courses has increased in a global scale. It has always been challenges in cooperating fast-changing software technologies, development methodologies and teamwork. Moreover, such project courses need to be designed in the connection to existing theoretical courses. We performed a large-scale research on student performance in Software Engineering projects in Norwegian universities. This paper investigates four aspects of team dynamics, which are team reflection, leadership, decision making and task assignment in order to improve student learning. Data was collected from student projects in 4 years at two universities. We found that some leader's characteristics are perceived differently for female and male leaders, including the perception of leaders as skilful workers or visionaries. Leadership is still a challenging aspect to teach, and assigned leadership is probably not the best way to learn. Students is are performing well in task review, however, needs support while performing task assignment. The result also suggests that task management to be done in more fine-grained levels. It is also important to maintain an open and active discussion to facilitate effective group decision makings.