After receiving his doctoral degree in computer science, he worked as a software engineer for an online storage service at an Internet services company. Since joining the university faculty, he has been conducting empirical software engineering research. His research group has collaborated with 58 companies in total under joint research contracts. He has supervised and supported 11 doctoral candidates who were also professional software engineers. He served as a council member for the Japanese Society for Quality Control, a chair of three working groups at the Information-technology Promotion Agency, a Japanese government-affiliated agency (2015-2018), and the committee chair for the Software Quality Symposium in Japan (2013-2024).
Speakers
Shuji Morisaki
Biography
About the KEYNOTE Presentation:
- Language: ENGLISH, Real time Japanese translation provided.
Leveraging actionable insights from testing, refined by cultural diversity, to enhance quality assurance and product value
Although the primary purpose of testing is to find bugs and verify their absence within the test scope, we can derive actionable testing insights leading to more efficient quality assurance activities and enhanced product value. Furthermore, most of the participants of this event also have gained insights from cultural diversity.
Firstly, this talk will demonstrate how sharing these insights with the team or improving the development process driven by these insights can lead to such efficiency and enhancement, helping audiences who have yet to fully leverage their insights.
Then, for those who are already leveraging these insights but find that only actionable insights lead to efficiency and enhancement, this talk will introduce criteria, based on effort and effectiveness, to identify actionable insights.
Specifically, this talk will explain an approach for leveraging bug insights for efficient quality assurance by categorising bugs and seeking the most appropriate detection technique. This talk will alsointroduce an approach for predicting product value by categorising user proficiency determined by user insights gained in testing.