This deposit provides the full Carlo multiâengine reasoning architecture, including both the conceptual Codex and the complete pseudocode implementation. Carlo defines a layered system of primitive operators, structural engines, operational cycles, metaâlayer analysis tools, constraint systems, extremeâcase stabilisers, adaptive reasoning modules, and workflow utilities. The entire framework is expressed in plain ASCII for maximum portability, transparency, and remixability. The full set of Carlo engines is useful for anyone exploring complex systems, reasoning architectures, or stateâbased transformations. Each engine contributes a distinct capability: some define primitive operations, some build structure, some manage operational flow, some analyse or predict behaviour, some enforce safety and constraints, some handle extreme conditions, and some adapt the system under stress. Together they form a modular, interoperable toolkit that can model processes, simulate trajectories, test contradictions, stabilise transformations, and support both human and machine reasoning. All components are designed to be readable, composable, and remixable, making the framework suitable for research, experimentation, teaching, prototyping, and building new computational models. This release includes the Carlo Superchain, a unified execution path that chains all engines into one continuous system flow. The Superchain is useful for anyone who wants a single, endâtoâend view of how the entire Carlo Framework runs. It is ideal for researchers, developers, and systems thinkers who need to understand the full lifecycle of a Carlo state, trace how each engine interacts, or build new tools on top of the architecture. The Carlo Super Chain Equation \[\mathcal{S} \;=\; E_n \circ E_{n-1} \circ \dots \circ E_2 \circ E_1\] \[x_{\text{final}} \;=\; \mathcal{S}(x_0)\] \[E_i \;=\; M_i \circ C_i \circ O_i\] \[\mathcal{S} \;=\;(M_n \circ C_n \circ O_n)\circ(M_{n-1} \circ C_{n-1} \circ O_{n-1})\circ\dots\circ(M_1 \circ C_1 \circ O_1)\] \[x_{k+1} \;=\; \mathcal{S}(x_k)\qquadx_k \;=\; \mathcal{S}^k(x_0)\] By chaining every operator, engine, constraint, metaâlayer tool, and adaptive module into one continuous execution flow, the Superchain provides a clear reference model for analysis, implementation, debugging, and experimentation. Because every transformation follows from defined operators and engine rules â with no external assumptions or hidden mechanisms â the Superchain functions as the structural proof of the framework. It demonstrates that the entire Carlo system is coherent, derivable, and complete. Engines: Primitive Operators Engine (core actions: collapse, propagate, reflect, reset) Early Loop Forms Engine (safe looping patterns and stabilisation cycles) Base Constraints Engine (fundamental safety and validity rules) Layering Engine (stacked processing layers that donât overwrite each other) Recursion Engine (safe, bounded recursive transformations) Multi Trajectory Engine (branching into multiple possible futures) State Space Compression Engine (reducing complexity without losing meaning) Carlo Visual Language Engine (ASCIIâsafe symbolic representation) Big Daddy Engine V2 (full structural architecture of the system) Full Nelson Engine (maximumâintensity transformation cycle) Hybrid Engines (structural + operational behaviour combined) Execution Pattern Engines (reusable operator sequences) Operational Engine Wrapper (selects and runs operational modes) Predictive Loop Mapper (forecasts loop behaviour and stability) Contradiction Compass (measures contradiction direction and magnitude) Trajectory Simulator (explores possible futures without choosing one) Cognitive Model (analyses how the system thinks) Meta Layer Engine Wrapper (unified access to all metaâlayer tools) Boundary Engine (keeps values and structures within safe limits) Validity Engine (ensures states are wellâformed and coherent) Loop Safety Engine (prevents infinite or unsafe loops) Collapse Safety Engine (ensures collapse never destroys essentials) State Space Guardrail Engine (prevents explosion or trivial collapse) Constraint Engine Wrapper (runs all constraint checks together) Infinity Engine (handles unbounded growth) Zero Engine (handles collapse to emptiness) Overload Engine (handles too much input or contradiction) Total Contradiction Engine (handles maximum conflict conditions) No Contradiction Engine (prevents overâcompression and stagnation) Degenerate Engine (repairs malformed or broken states) Extreme Case Engine Wrapper (runs all extremeâcase handlers) Fuck Cancer Engine VâOmegaâInfinityâAdaptive (maximum adaptive stabilisation) Adaptive Trajectory Simulator (stressâaware future exploration) Adaptive Cognitive Model (stressâresponsive reasoning analysis) AI Reasoning Engine (adaptive rule interpretation and inference) Adaptive Engine Wrapper (unified adaptive behaviour) Minimal Working Example (smallest runnable Carlo flow) Barebones Template (universal engine skeleton) Universal Execution Flow (master lifecycle of a Carlo state) HTML Rendering Engine (browserânative visualisation) Workflow Engine Wrapper (entry point for workflow tools) Appendices (diagrams, notes, glossary, future extensions) Keywords:Super Chain Loop; CarloâWilliams Engine; Carlo Framework; Carlo Visual Language; Carlo Reset Operator; Carlo Trajectory Simulator; Carlo Cognitive Model; Carlo AI Reasoning Engine; Universal Pseudocode; Engine Architecture; Operator Engine; Loop Dynamics; Recursive Systems; MetaâRecursive Structures; Emergent Behaviour; System Flow Analysis; Computational Physics; Theoretical Computation; Abstract Machine Design; Adaptive Engine Models; Dynamic State Machines; State Transition Logic; HighâOrder Looping; Feedback Loop Theory; Superposition Loops; ChainâLinked Operators; MultiâLayer Engine Design; Extreme Case Demonstrations; Minimal Working Example; Barebones Engine Template; Master Trajectory Update; Observational Tool Order; Predictive Loop Mapper; Contradiction Compass; Emergence Synthesiser; Stability Analysis; Nonlinear Systems; Complexity Theory; Information Flow; Symbolic Computation; Mathematical Modelling; Algorithmic Structures; Process Automation; Simulation Frameworks; PhysicsâCoded Computation; Computational Abstractions; Formal Systems; MetaâSystems Engineering; SelfâReferential Systems; Iterative Engine Design; HighâDimensional Operators; ConstraintâDriven Dynamics; Adaptive Feedback; Systemic Coherence; Structural Invariants; Computational Semantics; Engine Index; Core Definitions; System Overview; Trajectory Mapping; Loop Collapse Theory; Super Chain Loop Mechanics; ChainâLoop Coupling; Nested Loop Structures; Operator Hierarchies; MultiâStage Execution; Execution Pathways; Computational Topology; Symbolic Dynamics; Mathematical Operators; CalculusâLinked Engine Design; Differential System Flow; Integral Loop Behaviour; RateâofâChange Operators; Continuity Constraints; DiscreteâContinuous Hybrid Models; MetaâEngine Construction; Framework Synthesis; Research Tools; Open Science; Zenodo Research; Computational Frameworks; PhysicsâInspired Engines; The Original Loop; Volume Series; Technical Documentation; Engine Specification; Advanced System Design; HighâLevel Abstractions; Scientific Computing; Experimental Frameworks; OpenâSource Engine Research; Future Extensions; Engine Evolution; Adaptive Modelling; CognitiveâInspired Computation; Theoretical Engine Development; Research Infrastructure; Scientific Metadata; Academic Discovery; Knowledge Systems; Computational Reasoning; Symbolic Logic; Formal Verification; System Integrity; Process Coherence; MultiâOperator Chains; Super Chain Loop Integration; EngineâLevel Recursion; Recursive Operator Networks; HighâOrder Engine Behaviour; MetaâLoop Execution; CrossâLayer Dynamics; Computational Architecture; Systemic Feedback; LoopâDriven Computation; EngineâScale Modelling; Abstract Dynamics; Mathematical Foundations; ResearchâGrade Engine Design; Open Research Metadata; Scientific Keywords; Advanced Loop Theory; ChainâReaction Computation; OperatorâLinked Systems; EngineâWide Synchronisation; Temporal Dynamics; Causal Flow Mapping; Structural Loop Analysis; Computational Trajectories; EngineâBased Reasoning; SystemâLevel Abstractions; HighâFidelity Engine Models; Super Chain Loop Expansion; EngineâIntegrated Frameworks; Unified Engine Theory; Computational MetaâFramework; Scientific Engine Toolkit; Carlo Engine Ecosystem
Walter Kurz, Michel Malara, Wojtek Stricker, Eva Albrecht
The objective of this study is to define a compliance-first, conceptually generalisable architecture for a multi-agent artificial intelligence platform integrated with distributed ledger technology, designed to be domain-, deployment-, and vendor-agnostic. It addresses a persistent shortcoming in current AI deployments, where compliance is often treated as a secondary concern, applied retroactively through prompt engineering rather than embedded within the foundational design. The proposed model encodes regulatory, governance, and ESG requirements into an objective-under-constraints framework, ensuring that all specialised agents operate within legally admissible and verifiably auditable parameters prior to any domain-specific implementation. A DAG-based verification layer is incorporated to enable scalable, low-latency, and cost-efficient operation while preserving evidentiary integrity. The analysis evaluates the feasibility of this conceptual model to support sustainable, rapid-deployment vertical applications without inducing vendor lock-in, preserving operational neutrality, and ensuring environmental accountability. The findings suggest that integrating compliance, ESG metrics, and agent specialisation at the architectural level provides a transferable foundation for cross-domain AIâDLT infrastructures.
Dec 23, 2025·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Oliver Alexy, Oliver Baumann, Ying-Ying Hsieh, Giorgia SampĂł
Decentralized Autonomous Organizations (DAOs) represent a radical form of socio-technical systems, where rules are enforced by code and governance is conducted by a distributed network of stakeholders. A critical challenge in designing these systems is achieving consensus without centralized authority, yet how consensus ensures effective governance remains underexplored. This study investigates the design of DAO governance systems, utilizing data from 70 DAOs and applying Fuzzy Set Qualitative Comparative Analysis (fsQCA) to explore which consensus configurations lead to positive organizational outcomes. Our analysis challenges the notion of a single consensus model. Instead, we uncover 13 distinct configurations that characterize successful DAOs. Our key finding reveals a fundamental âideation-legitimation trade-offâ: successful DAOs optimize for broad participation in either the proposal (ideation) stage or the voting (legitimation) stage, but rarely both. These insights provide a nuanced framework for understanding and designing effective governance systems for DAOs.
Distributed Ledger Technology (DLT) engineering practices commonly rely on the adaptation and development of components as key building blocks. However, incorrect component specifications can lead to architectural flaws, which may propagate to implementation stages and result in faulty configurations. To address this, we build on declarative modeling techniques from program verification and refactoring to formally specify DLT components and their architectural composition. We introduce a component-based approach, Alloy4CMD , for the formal modeling and analysis of DLT architectural design. This approach maps individual components into well-formed formal specifications, enabling decidable (bounded) reasoning and property checking. We further employ a lattice-based abstract interpretation to approximate component semantics, with verification carried out in Alloy through assertions expressing conformance to requirements. The analysis involves automated model finding with bounded consistency checks using the Alloy Analyzer. Our approach provides validated, reusable modules, composes them into a validated architectural meta-model that supports early-stage DLT architectural design, and is independent of any particular DLT platform.
The sheer rampant growth of artificial intelligence (AI) systems in the safety-critical, regulated, and large-scale areas of infrastructures has enhanced the demand of deployment models that are secure, ethical compliant, and scalable in terms of operation. The proposed research aims to develop a layered AI system architecture with verifiable privacy, federated orchestration, and explanation of decision-making as the first principles, as opposed to an afterthought. The framework consists of three modular parts, namely a privacy preserving computational substrate based on holomorphic encryption (HE) and differential privacy (DP), a distributed trust model that is enforced by a zero knowledge proofs (ZKP) and decentralized authentication protocols, and an ethical governance layer that includes policy-aware execution and explainable AI (XAI) reasoning. In contrast to the isolated sandbox setup, this architecture was tried in the realistic environment of a deployment using the representative of the domain data, such as OpenAQ sensor telemetry, MIMIC-III health logs, or smart energy grid datasets. The simulations were performed on 60-node Docker Swarm cluster using orchestrated adversarial attacks such as input reconstruction, consensus disruption, and metadata inference. Based on empirical evidence, the results indicate the latency stabilization at less than 140 ms, the cryptographic computation overhead at less than 22 percent and the privacy leakage reduction at more than 83 percent compared to centralized conventional baselines. These results confirm the correctness of implementing scalable AI solutions and not compromising ethical outcomes, regulatory guidance, and computational performance. This is the stepping block of future AI infrastructures that will have to be at scale, constrained, and in a similar spirit as the human-centric values.
AI's merger with Web3 tech is changing the game leading to open, see-through, and somewhat self-running systems. This research explores the AI-agent paradigm in Web3 considering spread-out networks, blockchain rules, smart deals, and partial self-rule as new concepts. The main focus of this paper is to redefine the integration of artificial intelligence (AI) with Web3 technologies and create a semi-autonomous architecture that transcends decentralized and centralized approaches. While the majority of literature surveys AI agents that function on blockchain and decentralized protocols, our study presents a layered model that exploits off-chain AI inference with on-chain consensus mechanisms, (DID) management, and governance. We explain the main components, such as shared record-keeping, distributed ID management, reward systems, and agreement methods, that allow AI agents to function efficiently in the absence of a central boss. Moreover, the research analyzes significant issues such as scalability, safety, data privacy, and interoperability. It offers a number of improvements in off-chain AI-based agents for decentralized environments. Results demonstrate that hybrid on-chain/off-chain AI clusters can reduce inference costs and increase transaction throughput while preserving decentralization and data privacy. The team-up of AI and Web3 opens doors to new uses like spread-out money systems (DeFi), self-running groups (DAOs), and marketplaces without middlemen creating tough, clear, and user-focused digital worlds.
This chapter describes the macro context for the soft aesthetic experience through an exploratory overview of emerging and current shifts within three macro areas: Society and Culture, Science and Technology and Design and Aesthetics. The aim of this section is to set a foundation for the book through graspable explanations of pivotal moments influencing soft, not only as a design aesthetic but also as a movement, a quality of life and a platform for the future. The first section âsoft in Society and Cultureâ brings to the forefront important and current influential topics such as the emergence and prevalence of soft power, soft skills and a non-compartmentalized way of thinking and taking action in order to solve pressing problems. The second section âsoft in Science and Techâ, examines recent developments propelled by the emergence of movements such as The Fourth Industrial Revolution and technologies including Web3, 5G and 6G, articulated in the context of the book, together with important neuroscientific models including the Aesthetic Triad and scientific tools for mapping and visualizing emotions. The third section âsoft in Design and Aestheticsâ, explores practices such as sensory design through a new light to include a broader spectrum of senses and their interactions through sensory experiences. Emerging design areas such as The Aesthetics of Wellbeing, Sensory Restoration and Soft Rooms are also explored.
The objective of this study is to define a compliance-first, conceptually generalisable architecture for a multi-agent artificial intelligence platform integrated with distributed ledger technology, designed to be domain-, deployment-, and vendor-agnostic. It addresses a persistent shortcoming in current AI deployments, where compliance is often treated as a secondary concern, applied retroactively through prompt engineering rather than embedded within the foundational design. The proposed model encodes regulatory, governance, and ESG requirements into an objective-under-constraints framework, ensuring that all specialised agents operate within legally admissible and verifiably auditable parameters prior to any domain-specific implementation. A DAG-based verification layer is incorporated to enable scalable, low-latency, and cost-efficient operation while preserving evidentiary integrity. The analysis evaluates the feasibility of this conceptual model to support sustainable, rapid-deployment vertical applications without inducing vendor lock-in, preserving operational neutrality, and ensuring environmental accountability. The findings suggest that integrating compliance, ESG metrics, and agent specialisation at the architectural level provides a transferable foundation for cross-domain AI-DLT infrastructures.
The Zupply framework introduces an anonymous authentication protocol that utilizes zero-knowledge proofs to ensure data integrity, participant anonymity, and unlinkability within supply chains. Zupply employed the Groth16 zkSNARK, which requires a trusted setup. This paper explores the integration of Aurora, a transparent setup post-quantum secure zkSNARK, to the Zupply framework. This paper presents the core Zupply arithmetic circuits, including Auth, Trans, Merge, and Div, which allows succinct zero-knowledge proofs without exposing sensitive data. We evaluate the performance of the Zupply Aurora-based implementation across varying Merkle hash tree depths, comparing it to the original Groth16-based setup for BN254 and BLS12-381 elliptic curves.
Certified computer systems are becoming the key in the increasingly complex decision making activities of our modern society. Among others, error-free and secure solutions are indispensable within AI, Autonomous Systems, Big Data, Blockchain, Decentralized Finance (DeFi), or Cloud Computing. While the explosion in applications of computer systems leads to great increases in productivity, wealth, and convenience, it creates a paradoxical situation: we rely on computer systems despite that uncountable many scenarios showcase that computer systems are not (properly) certified and hence are error-prone. The area of automated reasoning provides computer-aided solutions to prove that computer systems are error-free, just like we prove theorems in mathematics. However, who can tell software developers which automated reasoning solutions should be used? Moreover, which reasoning method is best to be used during code review, for ensuring system safety and security? This talk will reflect on some challenges of automated reasoning and focus on concrete applications of system verification security. We will highlight aspects of open-source code development, allowing others to easily use our solutions in their technologies without the need of becoming experts in automated reasoning.
Cross-organizational, blockchain-based distributed ledger networks in general, and those based on Hyperledger Fabric in particular, have an architecture which can be adapted to specific application requirements. However, network design can be a particularly challenging task, as the connection between architectural and deployment decisions and extra-functional properties can be subtle and the requirements may contradict each other, requiring trade-offs.
We are currently witnessing the proliferation of blockchain environments to support a wide spectrum of corporate applications through the use of smart contracts. It is of no surprise that smart contract programming language technology constantly evolves to include not only specialized languages such as Solidity, but also general purpose languages such as GoLang and JavaScript. Furthermore, blockchain technology imposes unique challenges related to the monetary cost of deploying smart contracts, and handling roll-back issues when a smart contract fails. It is therefore evident that the complexity of systems involving smart contracts will only increase over time thus making the maintenance and evolution of such systems a very challenging task. One solution to these problems is to approach the implementation and deployment of such systems in a disciplined and automated way. In this paper, we propose a model-driven approach where the structure and inter-dependencies of smart contract, as well as stakeholder objectives, are denoted by extended goal models which can then be transformed to yield Solidity code that conforms with those models. More specifically, we present first a Domain Specific Language (DSL) to denote extended goal models and second, a transformation process which allows for the Abstract Syntax Trees of such a DSL program to be transformed into Solidity smart contact source code. The transformation process ensures that the generated smart contract skeleton code yields a system that is conformant with the model, which serves as a specification of said system so that subsequent analysis, understanding, and maintenance will be easier to achieve.
Research on blockchains addresses multiple issues, with one being the automated creation of smart contracts. Developing smart contract methods is more difficult than mainstream software development as the underlying blockchain infrastructure poses additional complexity. We report on a new approach to developing smart contracts with the objective of automating the process to increase developer efficiency and reduce the risk of errors introduced by software developers. To support industry adoption, we use Business Process Model and Notation (BPMN) modeling to describe an application while targeting applications in the trade vertical. We describe a system that transforms a BPMN model into a multi-modal model that combines Discrete Event (DE) modeling for concurrency with Hierarchical State Machines (HSMs) to represent application functionality. Then, further transformations are used to transform the DE-HSM model into methods in smart contracts. The system lets the modeler decide which of the independent patterns should be transformed into methods of a separate smart contract that is deployed on a sidechain for the purpose of (i) reducing processing costs and/or (ii) providing privacy so that other participants in the smart contract do not have visibility into the processing of the pattern. We also briefly describe a proof-of-concept tool we built to demonstrate the feasibility of our approach.
<p indent="0mm">Software is the core component of IT industry and an important âinfrastructureâ that supports social operations in the digital economy era. Since the 21st century, the internet has evolved into a global ubiquitous computing environment and open platform. Its open, dynamic, and uncontrollable nature requires the corresponding changes in the basic form and characteristics of software, the conceptual framework, and the logical connotation, and thus leads to substantial challenges to software theory, methods, and technologies. In 2000, researchers from China proposed the term âinternetwareâ, which indicates a new software paradigm for the internet computing. After more than <sc>20 years</sc> of efforts, a series of important research achievements have been made in aspects of the basic model, development methodology, runtime support, quality assessment and assurance of internetware, and resulted in systematic innovation results and produced a wide range of academic and industrial impacts. In internetware, the software model consists of a set of autonomous software entities distributed and/or decentralized over the internet and other extensions like internet of things and 4G/5G, together with a set of connectors for enabling collaborations among these entities in various ways. Internetware software entities are able to sense dynamic changes of the underlying environments, and continuously adapt to these changes by means of structural and behavioral maintenance and evolution. From the micro perspective, internetware software entities collaborate with each other on demand and on the fly. From the macro perspective, the entities can self-organize to form an application or community of interest and even decentralized autonomous organizations. As a result, the development and evolution of a software application with internetware can be viewed as continuous and iterative composition of various âdisorderedâ resources into âorderedâ software applications. Thus, software development with internetware is a process being bottom-up, inside-out, spiral, and to some extent, similar with the complex adaptive systems. For example, the internetware paradigm proposed the theory of software architecture modeling (called ABC methodology) covering the whole life-cycle, where the core artifacts and activities of every single stage are unified into the software architecture model and its iterative refinement and transformation. In this way, the internetware paradigm greatly improves the efficiency and quality of software development and evolution. In addition, the internetware paradigm expands the software architecture from the development phase to the runtime, by proposing the concept of runtime software architecture (RSA). The RSA has been widely applied for a large number of information âsiloâ systems to enable the functionality and data interoperability. This solution is a significantly disruptive technical invention, or namely the âblack boxâ mode, based on the client-driven resource reflection mechanism to achieve automatic recovery of the system runtime architecture and automatic generation of data access interfaces. Compared to the traditional âwhite boxâ interoperability solution, the internetware paradigm eliminates the need of accessing source code, documentation, and original development team, and improves the interoperability efficiency between information silos, with more than 100X acceleration. This article reviews the research and practice of internetware from the perspective of software paradigm, following the internet computing environment and its extensions as a clue. It also discusses the future research outlook of internetware, especially for the ubiquitous computing environments and data centric technologies.
Seyed Hossein Haeri, Peter Thompson, Neil Davies, Peter Van Roy · 6 authors
This paper directly addresses a long-standing issue that affects the development of many complex distributed software systems: how to establish quickly, cheaply, and reliably whether they can deliver their intended performance before expending significant time, effort, and money on detailed design and implementation. We describe ÎQSD, 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 distinctive feature of outcome diagrams is that they capture the essential observational properties of the system, independent of the details of system structure and behaviour. The ÎQSD paradigm derives bounds on performance expressed as probability distributions encompassing all possible executions of the system. The ÎQSD 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. ÎQSD has been successfully used by a small team in 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 worth billions of US dollars. The paper outlines the ÎQSD paradigm, describes its formal underpinnings, and illustrates its use via a topical real-world example taken from the blockchain/cryptocurrency domain. ÎQSD has supported the development of an industry-leading proof-of-stake blockchain implementation that reliably and consistently delivers blocks of up to 80 kB every 20 s on average across a globally distributed network of collaborating block-producing nodes operating on the public internet.
Piero Fraternali, Sergio Luis Herrera GonzĂĄlez, Matteo Frigerio, Mattia Righetti
Distributed Ledger Technology (DLT) is one of the most durable results of virtual currencies, which goes beyond the financial sector and impacts business applications in general. Developers can empower their solutions with DLT capabilities to attain such benefits as decentralization, transparency, non-repudiability of actions and security and immutability of data assets, to the price of integrating a distributed ledger framework into their software architecture. Model-Driven Development (MDD) is the discipline that advocates the use of abstract models and of code generation to reduce the application development and integration effort by delegating repetitive coding to an automated model-to-code transformation engine. In this paper, we explore the suitability of MDD to support the development of hybrid applications that integrate centralized database and distributed ledger architectures and describe a prototypical tool capable of generating the implementation artefacts starting from a high-level model of the application and its architecture.
Seyed Hossein Haeri, Peter Thompson, Neil Davies, Peter Van Roy · 6 authors
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 &Delta;QSD, 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 &Delta;QSD 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. &Delta;QSD 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 &Delta;QSD 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.
Seyed Hossein Haeri, Peter Thompson, Neil Davies, Peter Van Roy · 6 authors
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 ÎQSD, 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 ÎQSD 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. ÎQSD 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 ÎQSD 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.
Scalability, privacy, and interoperability are some of the major issues receiving attention in research on blockchain technologies. We concentrate on the trade finance vertical for which we develop a new modeling approach with the objective of automatic transformation of an application, represented using Business Process Model and Notation (BPMN), into a smart contract deployed on a blockchain. Here, we describe how the BPMN model is transformed into a multimodal model that combines DE-HSM modeling. We provide a high-level overview of the method and review how BPMN categories of elements are transformed into a multi-modal DE-HSM model. We also describe briefly how the DE-FMS model is automatically transformed into deployable smart contracts that interact to form a distributed application: The smart contract deployed on the main blockchain coordinates activities amongst the business partners and interoperates with smart contracts, also automatically prepared and deployed on a sidechain(s), with one smart contract per individual business partner. Privacy is obtained by performing activities, which are not germane to the collaboration with the other business partners but deal with the private activities of the individual business partner, in a smart contract deployed and executed on a side chain. We thus provide for interoperability of smart contracts and privacy as private activities of a business partner are performed in a smart contract on a private sidechain.
Service fulfillment for clients increasingly involves cooperation between information technology (IT) systems. Designing such solutions requires an architectural approach that ensures symmetry between the communicating parties. For the design of such systems, the author introduces the 1+5 architectural views model. The model contains three new architectural views. For business process modeling, it ensures the integrated processes view. Integration aspects cover two additional views: integrated services, and contracts. Moreover, new stereotypes and tagged values have been added to the unified modeling language (UML). The author has introduced two profiles: UML profile for integration flows, and UML profile for distributed ledger deployment. Communication between systems requires flows that arrange mediation mechanisms. The paper describes an integration flow diagram that extends a UML activity diagram. In the case of blockchain, the author has proposed the smart contract design pattern. The paper describes three case studies that have employed the model to design various solutions. The 1+5 model has proven to be well suited for designing both centralized integration environments with enterprise service bus (ESB) and distributed blockchain solutions with peer-to-peer (P2P) connections.