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Supporting the Exploration of Quality Attribute Tradeoffs in Large Design Spaces

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Software Architecture (ECSA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14212))

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Abstract

When designing and evolving software architectures, architects need to consider large design spaces of architectural decisions. These decisions tend to impact the quality attributes of the system, such as performance, security, or reliability. Relevant quality attributes might influence each other and usually need to be traded off by architects. When exploring a design space, it is often challenging for architects to understand what tradeoffs exist and how they are connected to architectural decisions. This is particularly problematic in architectural spaces generated by automated optimization tools, as the underlying tradeoffs behind the decisions that they make are unclear. This paper presents an approach to explore quality-attribute tradeoffs via clustering and visualization techniques. The approach allows architects to get an overview of the main tradeoffs and their links to architectural configurations. We evaluated the approach in a think-aloud study with 9 participants from academia and industry. Our findings show that the proposed techniques can be useful in understanding feasible tradeoffs and architectural changes affecting those tradeoffs in large design spaces.

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Notes

  1. 1.

    A tactic decreaseCapacity(?device) that reverses the effects of adding a service to a device can be also considered in the graph.

  2. 2.

    In case of sequences of different lengths, we pad the shorter sequence with a special noOp()  tactic that makes no changes to the architectural configurations.

  3. 3.

    Notebook: https://shorturl.at/jyCX3 - Tasks: https://shorturl.at/lHU08.

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Acknowledgements

This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program funded by the Knut and Alice Wallenberg Foundation. It was also supported by project PICT-2021-00757.

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Authors and Affiliations

  1. ISISTAN Research Institute, CONICET and UNICEN University, Tandil, Buenos Aires, Argentina

    J. Andres Diaz-Pace

  2. Department of Computer Science and Engineering, Chalmers University of Gothenburg, Gothenburg, Sweden

    Rebekka Wohlrab

  3. Software and Societal Systems Department, Carnegie Mellon University, Pittsburgh, PA, USA

    David Garlan

Authors
  1. J. Andres Diaz-Pace
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  2. Rebekka Wohlrab
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  3. David Garlan
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Corresponding author

Correspondence to J. Andres Diaz-Pace .

Editor information

Editors and Affiliations

  1. Wageningen University, Wageningen, The Netherlands

    Bedir Tekinerdogan

  2. Computer Science, Gran Sasso Science Institute, L’Aquila, Italy

    Catia Trubiani

  3. LIRMM, University of Montpellier, Montpellier, France

    Chouki Tibermacine

  4. DIGIP, University of Bergamo, Dalmine, Italy

    Patrizia Scandurra

  5. Superior de Ingeniería Informática, Rey Juan Carlos University, Mostoles, Madrid, Spain

    Carlos E. Cuesta

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Diaz-Pace, J.A., Wohlrab, R., Garlan, D. (2023). Supporting the Exploration of Quality Attribute Tradeoffs in Large Design Spaces. In: Tekinerdogan, B., Trubiani, C., Tibermacine, C., Scandurra, P., Cuesta, C.E. (eds) Software Architecture. ECSA 2023. Lecture Notes in Computer Science, vol 14212. Springer, Cham. https://doi.org/10.1007/978-3-031-42592-9_1

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  • DOI: https://doi.org/10.1007/978-3-031-42592-9_1

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  • Online ISBN: 978-3-031-42592-9

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