An Empirical Study on Collaborative Architecture Decision Making in Software Teams
July 01, 2017 Β· Declared Dead Β· π European Conference on Software Architecture
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Sandun Dasanayake, Jouni Markkula, Sanja Aaramaa, Markku Oivo
arXiv ID
1707.00107
Category
cs.SE: Software Engineering
Citations
3
Venue
European Conference on Software Architecture
Last Checked
4 months ago
Abstract
Architecture decision making is considered one of the most challenging cognitive tasks in software development. The objective of this study is to explore the state of the practice of architecture decision making in software teams, including the role of the architect and the associated challenges. An exploratory case study was conducted in a large software company in Europe and fifteen software architects were interviewed as the primary method of data collection. The results reveal that the majority of software teams make architecture decisions collaboratively. Especially, the consultative decision- making style is preferred as it helps to make decisions efficiently while taking the opinions of the team members into consideration. It is observed that most of the software architects maintain a close relationship with the software teams. Several organisational, process and human related challenges and their impact on architecture decision-making are also identified.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted