Human Aspects of Software Engineering Lab
About HASEL
The Human Aspects of Software Engineering Lab at the University of Auckland carries out research projects focused on improving software practices and processes. Our goal is to make it easier (and more fun!) for software teams to create user-friendly products. For example, we study ways to improve coordination on software teams, investigate novel techniques to help software developers understand what users want from the software, and study software developer work patterns. We employ a variety of both qualitative and quantitative research methods including developing new methods and tools, data mining, repository analysis, social network analysis, interviews, surveys, and lab experiments.
We are also interested in leveraging deep learning algorithms to build innovative software systems aiming to enable the disabled. Among these interests are enabling computers to understand individuals suffering from speech impairments to act as a communication medium on their behalf, improving and expediating the identification of autistic individuals, and other related assistive technologies that fall in similar scope.
Recent News
Associate Professor Ewan Tempero wins Most Influential Paper Award
HASEL member, Associate Professor Ewan Tempero, received the Most Influential Paper award at Asia Pacific Software Engineering Conference (APSEC) 2023, held in Seoul, South Korea. The award recognised a paper published at APSEC 2010, titled “The qualitas corpus: A...
Dhanushka Jayasuriya wins Best Student Research Award
HASEL member, Dhanushka Jayasuriya, won the Best Student Research Award at the Australasian Software Engineering Summer School (ASESS) 2024 held in Sydney, Australia last week. More than 20 students presented their work at the conference. Dhanushka is a third year PhD...
ENGclusion longitudinal study starts
Associate Professor Kelly Blincoe's ENGclusion longitudinal study has started! The first questionnaire for the study is now up, and the ENGclusion team are collecting their first round of data. Their goal is to understand how to retain historically excluded groups in...
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