Poster: Making Well-Informed Software Design Decisions
by Arman Shahbazian, Youn Kyu Lee, Yuriy Brun, Nenad Medvidovic
Abstract:
Design decisions software architects make directly impact system quality. Real-world systems involve a large number of such decisions, and each decision is typically influenced by others and involves trade-offs in system properties. This paper poses the problem of making complex, interacting design decisions relatively early in the project's lifecycle and outlines a search-based and simulation-based approach for helping architects make these decisions and understand their effects.
Citation:
Arman Shahbazian, Youn Kyu Lee, Yuriy Brun, and Nenad Medvidovic, Poster: Making Well-Informed Software Design Decisions, in Proceedings of the Poster Track at the International Conference on Software Engineering (ICSE), 2018, pp. 262–263.
Bibtex:
@inproceedings{Shahbazian18icse-poster,
  author = {Arman Shahbazian and Youn Kyu Lee and Yuriy Brun and Nenad Medvidovic},
  title = {\href{http://people.cs.umass.edu/brun/pubs/pubs/Shahbazian18icse-poster.pdf}{Poster: 
  {Making} Well-Informed Software Design Decisions}},
  booktitle = {Proceedings of the Poster Track at the International
  Conference on Software Engineering (ICSE)},
  venue = {ICSE Poster},
  address = {Gothenburg, Sweden},
  month = {May},
  date = {30--1},
  year = {2018},
  accept = {$\frac{297}{397} \approx 75\%$},
  doi = {10.1145/3183440.3194961},  
  note = {\href{https://doi.org/10.1145/3183440.3194961}{DOI: 10.1145/3183440.3194961}},
  pages = {262--263},

  abstract = {Design decisions software architects make directly impact
  system quality. Real-world systems involve a large number of such
  decisions, and each decision is typically influenced by others and involves
  trade-offs in system properties. This paper poses the problem of making
  complex, interacting design decisions relatively early in the project's
  lifecycle and outlines a search-based and simulation-based approach for
  helping architects make these decisions and understand their effects.},

  fundedBy = {NSF CCF-1564162, NSF CCF-1618231, Huawei Technologies Co., Ltd.}
}