Mind Your Outcomes:  The ∆Q approach to Quality-Centric Systems Development and Its Application to a Blockchain Case-Study

Seyed Hossein HAERI; Peter Thompson; Neil Davies; Peter Van Roy; Kevin Hammond; James Chapman

doi:10.20944/preprints202112.0132.v2

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preprints.org > computer science and mathematics > computer science > doi: 10.20944/preprints202112.0132.v2

Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Mind Your Outcomes: The ∆Q approach to Quality-Centric Systems Development and Its Application to a Blockchain Case-Study

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Version 1 : Received: 7 December 2021 / Approved: 8 December 2021 / Online: 8 December 2021 (14:25:02 CET)
Version 2 : Received: 16 December 2021 / Approved: 21 December 2021 / Online: 21 December 2021 (13:59:45 CET)
Version 3 : Received: 21 January 2022 / Approved: 24 January 2022 / Online: 24 January 2022 (11:43:32 CET)

A peer-reviewed article of this Preprint also exists.

Haeri, S.H.; Thompson, P.; Davies, N.; Van Roy, P.; Hammond, K.; Chapman, J. Mind Your Outcomes: The ΔQSD Paradigm for Quality-Centric Systems Development and Its Application to a Blockchain Case Study. Computers 2022, 11, 45. Haeri, S.H.; Thompson, P.; Davies, N.; Van Roy, P.; Hammond, K.; Chapman, J. Mind Your Outcomes: The ΔQSD Paradigm for Quality-Centric Systems Development and Its Application to a Blockchain Case Study. Computers 2022, 11, 45.

Abstract

This paper directly addresses a critical issue that affects the development of many complex distributed software systems: how to establish quickly, cheaply and reliably whether they will deliver their intended performance before expending significant time, effort and money on detailed design and implementation. We describe ΔQSD, a novel metrics-based and quality-centric paradigm that uses formalised outcome diagrams to explore the performance consequences of design decisions, as a performance blueprint of the system. The ΔQSD paradigm is both effective and generic: it allows values from various sources to be combined in a rigorous way, so that approximate results can be obtained quickly and subsequently refined. ΔQSD has been successfully used by Predictable Network Solutions for consultancy on large-scale applications in a number of industries, including telecommunications, avionics, and space and defence, resulting in cumulative savings of $Bs. The paper outlines the ΔQSD paradigm, describes its formal underpinnings, and illustrates its use via a topical real-world example taken from the blockchain/cryptocurrency domain, where application of this approach enabled an advanced distributed proof-of-stake system to meet challenging throughput targets.

Keywords

formal semantics; quality attenuation; distributed systems; system design; scalability; performance; feasibility; blockchain; ΔQ.

Subject

Computer Science and Mathematics, Computer Science

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Comments (1)

Comment 1

Received: 21 December 2021
Commenter: Peter Thompson
Commenter's Conflict of Interests: Author

Comment: Updated the title at the request of the Computers editor. Changed the symbol for convolution to be consistent with general usage. Fixed typos:
Table 1: Lomg -> LongPage 19: Is the headline "Alternative Refinements" formatted correctly?Page 22: In the list of the two steps, top of page, the Tau overlaps with the subscript Z and makes it hard to read.Also page 22: In the second sentence of the paragraph after the lists, there seems to be a missing word: "... the m (selected) neighbors of its are ..."Page 23: missing space, search for "thatZ"Page 25: Text says 90th centile, while plot shows 95th

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