Knowledge management and throughput optimization in large-scale software development
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Large-scale software development companies delivering market-driven products have introduced agile methodologies as the way of working to a big extent. Even though there are many benefits with an agile way of working, problems occur when scaling agile because of the increased complexity. One explicit problem area is to evolve deep product knowledge, which is a domain specific knowledge that cannot be developed anywhere else but at the specific workplace. This research aims to identify impediments for developing domain specific knowledge and provide solutions to overcome these challenges in order to optimize knowledge growth and throughput.
The result of the research shows that impediments occur in four different categories, based on a framework for knowledge sharing drivers. These are people-related, task-related, structure-related and technology-related. The challenging element with knowledge growth is to integrate the training into the feature development process, without affecting the feature throughput negatively.
The research also shows that by increasing the knowledge sharing, the competence level of the whole organization can be increased, and thereby be beneficial from many perspectives, such as feature-throughput and code quality.
Place, publisher, year, edition, pages
2015. , 74 p.
Knowledge management, software development, large-scale software development, throughput optimization, agile software development
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-119607ISRN: LIU-IDA/LITH-EX-A–15/025–SEOAI: oai:DiVA.org:liu-119607DiVA: diva2:824762
Subject / course
Sandahl, Kristian, Professor
Schmidt, Johannes, Universitetslektor