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An Evaluation Of The Use Of Software Engineering Practices By Cognitive Modelling Researchers

Oluşturulma Tarihi: 02-11-2018

Niteleme Bilgileri

Tür: Tez

Alt Tür: Yüksek Lisans Tezi

Yayınlanma Durumu: Yayınlanmamış

Dosya Biçimi: PDF

Dil: İngilizce

Konu(lar): TEKNOLOJİ,

Yazar(lar): Kurtaran, Furkan (Yazar),

Emeği Geçen(ler): Say, Bilge (Danışman),

Anahtar Kelimeler

cognitive modelling, scientific software, software engineering practices


Özet

As an instance of scientific software, cognitive modelling is used to reveal how brains work in different levels of abstraction. Although there have been studies of software engineering practices in other domains of scientific modelling, cognitive modelling has not been inspected from a software engineering point of view. An international online survey with cognitive modelling researchers has been carried to pinpoint relevant points as well as to see whether there were any self-stated differences between developers and modellers; or between high level cognitive modellers and computational neuroscientists in their software engineering practices.It has been found out that researchers in cognitive modelling, as in other scientific software domains, find frequent changes in teams to be problematic, specifying requirements to be hard, acknowledge the need for documentation and want to improve their software engineering practices. Participants find software engineering practices relevant, but their familiarity and level of use is lower, with the exception of version control and change management deemed both relevant and practiced. There are no significant differences between developers and modellers except for the observation that modellers stating themselves as more appreciative of validation. Similarly, no significant differences have been found between highivlevel cognitive modelling researchers and computational neuroscience researchers on their stated level of use of software engineering practices. However, researchers with larger team sizes use validation and verification more than those in smaller teams or working alone and larger user bases enhance the researchers’ use of issue and bug tracking.


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