My technical project is a web-based system design simulator app. Specifically, this project is an educational tool used to bridge the gap between industry expectation and the preparation of entry level software engineers. Through a turn-based simulation, users engage in experiential learning, showing how each decision made influences the immediate steps and system state, as well as how those decisions cascade in the more long-term project context. Each decision triggers a new event, allowing users to choose an option to address a given event. There is no clear âcorrectâ option but instead emphasizes tradeoffs and how those tradeoffs affect system architecture. The system architecture is exposed through two means. First, a metrics panel is presented to a user, with metrics like reliability, architecture complexity, performance, latency, and real-world constraints like budget. Secondly, a software architecture diagram is presented to the user as a main focus of the screen, allowing the user to refer to it for a visual representation of the internal system state as a level of abstraction expected in system design scenarios. Specifically, the software diagram has nodes and edges between the high-level components to represent major parts of a system. Both the metrics panel and software diagram update per decision, showcasing the current system state and highlighting the effect a decision had through. In particular, a slider representing the metrics tracked adjusts (via animation) and also provides color-themed feedback on the state of those metrics (âgoodâ, âwarningâ, âcriticalâ). Depending on the event, the system highlights relevant nodes and edges to indicate to the user where in the system the newest issue is, allowing users to focus on the problem area, but also maintain a perspective of the system at large, as to not lose focus of more long-term goals. The project includes multiple âworldsâ, which simulate a junior software engineer being assigned to a new project, and each world has its own events and action options to take. After playing a session, users can review their decisions to further inform their future decisions. My STS project explores the paths that governance power is redirected through in Decentralized Autonomous Organizations (DAOs). By juxtaposing the DAO imaginary with the realities limited by their implementation in practice, I expose the true outcome of their network. Specifically, I examine how proposed DAO theoretical attributes reveal themselves through a case study of CityDAO. While exploring the lifetime of CityDAO, I apply Actor Network Theory (ANT) to model CityDAO in particular (and DAO processes more broadly) as a network of human and non-human actors. In this network, each actor delegates a level of agency to each other actor it interacts with. I highlight how agency is assigned from each actor to others, and how each actor reshapes the ultimate outcome of the system. However, not all actors are equal. Rather, some actors function as obligatory passage points, through which all proposals must flow and cannot proceed unless this actor allows the proposal to proceed. Through my analysis, I identify membership NFTs, informal member forums, DAO members, DAO leaders, and formal vote signaling tools as actors in this actor network. I also identify multi-signature wallets, registered legal agents, and DAO-oriented legislation as obligatory passage points. By examining this network, I reveal the controlling role that multi-signature wallets, registered legal agents, and supporting DAO legislation plays in the proposal process. These obligatory passage points hold ultimate governance power, since if any of them fail or reject a proposal, the entire system process up until that pointâs intentions are unrealized. While not highly correlated in a direct way, these two projects complement each other by emphasizing system/network level perspectives of visualizing sociotechnical systems and processes. My technical project focuses on users building their understanding of system architecture, while my STS paper reveals the critical points where power lies in the DAO proposal process. Together, the system-building skills learned from the technical project may be applied alongside the strengths and limitations revealed through the network in the STS project to enable us to design systems that more adequately allocate power among all actors moving forward.
Open access
Software Engineering Techniques and Practices
Systems Engineering Methodologies and Applications
Matteo Vaccargiu, Sabrina Aufiero, Silvia Bartolucci, Ronnie de Souza Santos · 6 authors
Labels on platforms such as GitHub support triage and coordination, yet little is known about how well they align with code modifications or how such alignment affects collaboration across contributor experience levels. We present a case study of the Kubernetes project, introducing label-diff congruence - the alignment between pull request labels and modified files - and examining its prevalence, stability, behavioral validation, and relationship to collaboration outcomes across contributor tiers. We analyse 18,020 pull requests (2014--2025) with area labels and complete file diffs, validate alignment through analysis of over one million review comments and label corrections, and test associations with time-to-merge and discussion characteristics using quantile regression and negative binomial models stratified by contributor experience. Congruence is prevalent (46.6\% perfect alignment), stable over years, and routinely maintained (9.2\% of PRs corrected during review). It does not predict merge speed but shapes discussion: among core developers (81\% of the sample), higher congruence predicts quieter reviews (18\% fewer participants), whereas among one-time contributors it predicts more engagement (28\% more participants). Label-diff congruence influences how collaboration unfolds during review, supporting efficiency for experienced developers and visibility for newcomers. For projects with similar labeling conventions, monitoring alignment can help detect coordination friction and provide guidance when labels and code diverge.
Gerardo Iuliano, Daniele Carangelo, Carmine T. Calabrese, Dario Di Nucci
Mutation testing is a technique to assess the effectiveness of test suites by introducing artificial faults into programs. Although mutation testing plugins are available for many platforms and languages, none is currently available for Remix-IDE, the most widely used Integrated Development Environment for the entire contract development journey, used by users of all knowledge levels, and serves as a learning lab for teaching and experimenting with Ethereum. The quality and security of smart contracts are crucial in blockchain systems, as even minor issues can result in substantial financial losses. This paper proposes MuSe, a mutation testing plugin for the Remix-IDE. MuSe includes traditional, Solidity-specific, and security-oriented mutation operators. Its integration into the Remix-IDE eliminates the need for additional setup and lowers the entry barrier. As a result, developers and researchers can immediately leverage mutation testing to assess the effectiveness of their test suites and identify potential issues in smart contracts. We provide a demo video showing MuSe: https://www.youtube.com/watch?v=MIFk9exTDu0 and its repository: https://github.com/GerardoIuliano/MuSe-Remix-Plugin.
Large language models (LLMs) have been widely adopted in modern software development lifecycles, where they are increasingly used to automate and assist code generation, significantly improving developer productivity and reducing development time. In the blockchain domain, developers increasingly rely on LLMs to generate and maintain smart contracts, the immutable, self-executing components of decentralized applications. Because deployed smart contracts cannot be modified, correctness and security are paramount, particularly in high-stakes domains such as finance and governance. Despite this growing reliance, the security implications of LLM-generated smart contracts remain insufficiently understood. In this work, we conduct a systematic security analysis of Solidity smart contracts generated by state-of-the-art LLMs, including ChatGPT, Gemini, and Sonnet. We evaluate these contracts against a broad set of known smart contract vulnerabilities to assess their suitability for direct deployment in production environments. Our extensive experimental study shows that, despite their syntactic correctness and functional completeness, LLM-generated smart contracts frequently exhibit severe security flaws that could be exploited in real-world settings. We further analyze and categorize these vulnerabilities, identifying recurring weakness patterns across different models. Finally, we discuss practical countermeasures and development guidelines to help mitigate these risks, offering actionable insights for both developers and researchers. Our findings aim to support safe integration of LLMs into smart contract development workflows and to strengthen the overall security of the blockchain ecosystem against future security failures.
Smart contracts are high-stakes software: their immutable, publicly accessible, code may govern assets worth millions, meaning that even minor defects can have severe consequences. The most used techniques to ensure smart contract correctness are testing and formal verification. Testing is almost always employed but is often restricted to unit tests (which often miss edge cases) and has limited coverage, while formal verification can provide strong guarantees but is often costly and complex to apply, demanding substantial time and expertise. Property-based testing bridges this gap by exploring large input spaces and shrinking failures to minimal counterexamples, helping uncover defects early in development. Formal verification can be left to critical features once testing has filtered out common issues. To add to the challenges smart contract developers face, most languages used were not designed with safety and security guarantees built-in. Daml is a smart contract language designed with correctness in mind, featuring a strong static type system, functional programming paradigms, and built-in abstractions for common smart contract patterns. However, Daml currently lacks support for property-based testing, limiting developers' ability to systematically explore input spaces and verify contract properties. This paper introduces Hypothesis2Daml, an open-source library that brings property-based testing to the Daml ecosystem by connecting the Hypothesis testing framework with the Daml JSON API. Hypothesis2Daml enables developers to specify invariants, preconditions, and stateful workflows over realistic ledger interactions, while providing automatic input generation, shrinking, and isolation of ledger state between test cases. The approach is evaluated using a benchmark consisting of eight contracts, three Daml templates, and twenty-eight property-based tests covering happy paths, negative cases, and alternative interaction orders. The results show that property-based testing is feasible for Daml smart contracts, can systematically expose violated properties with minimal counterexamples, and supports effective debugging of realistic, stateful workflows.
Abstract Agile fosters speed, autonomy, and innovation at the team level, but organizations often struggle to preserve these strengths as they scale. Coordination overhead increases, decision-making slows, and the agility that once fueled success begins to erode. This paper introduces an approach to scaling by drawing on Robotics Subsumption Architecture , a model originally developed to build adaptive, autonomous robots. Building on the late Mike Beedle âs pioneering work in applying these robotics principles to organization design , we reimagine how to design systems that grow without sacrificing local autonomy or real-time responsiveness. This approach offers scalable agility by embedding sensing, decision-making, and action into every layerâresulting in organizations that are resilient, decentralized, and capable of surviving todayâs VUCA market.
Smart contract (SC) fuzzing is a critical technique for detecting vulnerabilities in blockchain applications. However, its adoption remains challenging for practitioners due to fundamental differences between SCs and traditional software systems. In this study, we investigate the challenges practitioners face when adopting SC fuzzing tools by conducting an inductive content analysis of 381 GitHub issues from two widely used SC fuzzers: Echidna and Foundry. Furthermore, we conducted a user study to examine how these challenges affect different practitioner groups, SC developers, and traditional software security professionals, and identify strategies practitioners use to overcome them. We systematically categorize these challenges into a taxonomy based on their nature and occurrence within the SC fuzzing workflow. Our findings reveal domain-specific ease-of-use and usefulness challenges, including technical issues with blockchain emulation, and human issues with a lack of accessible documentation and process automation. Our results provide actionable insights for tool developers and researchers, guiding future improvements in SC fuzzer tool design.
Abstract- The evolution of blockchain and Web3 technologies has paved the way for decentralized application platforms that enable transparent, tamper-proof transactions without relying on centralized servers. However, existing solutions such as Gitcoin and Giveth are either too complex or unsuitable for modular deployment in educational and lightweight environments. This paper proposes MetaSuite, a role-based, blockchain-driven Software-as-a-Service (SaaS) platform that enables users to create, transfer, and donate tokens while allowing an administrator to securely withdraw funds. Built entirely on the Ethereum blockchain using Solidity smart contracts, MetaSuite operates without a backend and integrates wallet-based authentication via MetaMask and Ethers.js. The platform ensures transparent fund management through on-chain event logging and role-based access controls. Performance evaluations on the Ethereum HoleskyTestnet demonstrate the systemâs reliability, gas-efficiency, and real-time responsiveness. By eliminating backend dependencies and emphasizing traceability, MetaSuite serves as a minimalistic yet scalable Web3 solution suitable for academic, experimental, and small-scale real-world deployments. KeywordsâBlockchain, Web3, Smart Contracts, Ethereum, MetaMask, Tokenization, SaaS, Ethers.js, Decentralized Applications.
The Hadamard product (also known as element-wise multiplication) is a fundamental operation in linear algebra, performed by multiplying corresponding elements of two matrices with the same dimensions. This operation plays a crucial role in various fields, including cryptography, where it enables efficient and parallelizable computations on large datasetsâparticularly in the design of cryptographic protocols such as zero-knowledge proofs. In this paper, we propose a transparent and efficient method for proving the Hadamard product between vectors that are independently committed in the groups G1and G2under a pairing operation e : G1ĂG2â GT . For a vector of length n, the prover has a complexity ofOλ(n), while the proof size isOλ(logn). The verifier operates with a complexity ofOλ(logn), which includesO(logn) operations in GT and onlyO(1) pairing operations, making verification highly efficient. We prove the security of our scheme under the Symmetric External Diffie-Hellman (SXDH) assumption. Furthermore, we propose an aggregator for Groth16 (EUROCRYPT 2016) zk-SNARKs and a proof aggregation technique for the general case of the KZG polynomial commitment scheme (ASIACRYPT 2010), where all crs are distinct. Both applications do not require an additional trusted setup, support logarithmic-sized aggregated proofs, and significantly reduce the verifierâs pairing operations toO(1).
Darja Ć mite, Nils Brede Moe, Marcin Floryan, Javier GonzĂĄlezâHuerta · 6 authors
While modern software companies strive to increase team autonomy to enable them to successfully operate the piece of software they develop and deploy, efficient ways to orchestrate the work of multiple autonomous teams working in parallel are still poorly understood. In this paper, we report how team autonomy is maintained at Spotify at scale, based on team retrospectives, interviews with team managers and archival analysis of corporate databases and work procedures. In particular, we describe how managerial authority is decentralized through various workgroups with collective authority, what compromises are made to team autonomy to ensure alignment and which team-related factors can further hinder autonomy. Our findings show that scaled autonomy at Spotify does not mean anarchy, or unlimited permissiveness. Instead, squads are expected to take responsibility for their work and coordinate, communicate and align their actions with others, and comply with a few enabling constraints. Further, squads take many decisions independently without management control or due to collective efforts that bypass formal boundary structures. Mechanisms and strategies that enable self-organization at Spotify are related to effective sharing of the codebase, achieving alignment, networking and knowledge sharing, and are described to guide other companies in their efforts to scale autonomy.
Architectural design contexts contain a set of factors that greatly influence software application development. Among them, organizational design contexts consist of high-level company concerns and how it is structured, for example, stakeholders and development schedules heavily impacting design considerations. The Decentralized Autonomous Organization (DAO), as a vital concept in the Web3 space, represents an organization constructed by automatically executed rules, such as via smart contracts, holding features of the permissionless committee, transparent proposals, and fair contribution by participated stakeholders. In this work, we conduct a systematic literature review of existing DAO literature to summarize its structural features, benefits and challenges, and potential development directions in the context of Web3 applications.
Learning heterogeneous graphs consisting of different types of nodes and edges enhances the results of homogeneous graph techniques. An interesting example of such graphs is control-flow graphs representing possible software code execution flows. As such graphs represent more semantic information of code, developing techniques and tools for such graphs can be highly beneficial for detecting vulnerabilities in software for its reliability. However, existing heterogeneous graph techniques are still insufficient in handling complex graphs where the number of different types of nodes and edges is large and variable. This paper concentrates on the Ethereum smart contracts as a sample of software codes represented by heterogeneous contract graphs built upon both control-flow graphs and call graphs containing different types of nodes and links. We propose MANDO, a new heterogeneous graph representation to learn such heterogeneous contract graphsâ structures. MANDO extracts customized meta-paths, which compose relational connections between different types of nodes and their neighbors. Moreover, it develops a multi-metapath heterogeneous graph attention network to learn multi-level embeddings of different types of nodes and their metapaths in the heterogeneous contract graphs, which can capture the code semantics of smart contracts more accurately and facilitate both fine-grained line-level and coarse-grained contract-level vulnerability detection. Our extensive evaluation of large smart contract datasets shows that MANDO improves the vulnerability detection results of other techniques at the coarse-grained contract level. More importantly, it is the first learning-based approach capable of identifying vulnerabilities at the fine-grained line-level, and significantly improves the traditional code analysis-based vulnerability detection approaches by 11.35% to 70.81% in terms of F1-score.
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 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.
GĂŒnther Schuh, Jan Hicking, Max-Ferdinand Stroh, Justus Benning
The number of available technologies is constantly rising. Be it additive manufacturing, artificial intelligence (AI) or distributed ledger technologies. The choice of the right technologies may decide the fate of a company. Due to the overwhelming amount of information sources, regular technology market research becomes increasingly challenging, especially for SMEs. In order to assist the technology management process, the authors will introduce the architecture of an automated, AI-based technology radar. The architecture will automatically collect data from relevant sources, assess the relevance of the respective technology (i.e. their maturity level) and then visualize it on the radar map.
Stakeholder participation is a cornerstone of effective Requirements Engineering (RE). It supports the development and evolution of software systems so that they fit their intended purpose within their application domain. To enable successful stakeholder participation RE experts have created a broad variety of approaches for different circumstances and project phases. These approaches focus on traditionally dedicated software systems, which have closed and location-bound user groups. The stakeholders of these systems usually are members of the organizations that commission or build the system. Meanwhile, technological development has opened doors for ubiquitously deployed and openly available software systems. Stakeholders of these systems are rarely members of those organizations. Instead, they are so-called outside organizational reach and typically unknown to RE experts. Hence, in contrast to stakeholders of traditionally dedicated software systems, they can neither straightforwardly be identified nor be requested to participate in RE. Moreover, they are likely location-independent, numerous and highly heterogeneous. Current RE approaches do not suffice to address these challenges. Established RE approaches provide limited means to identify stake- holders outside organizational reach, let alone motivate them to voluntarily participate in RE. They also cannot support collaboration in distributed settings or on a large scale, yet, collaboration is known to be essential for the development of novel systems and in unknown domains. Feedback mechanisms and social network sites enable distributed and large-scale collaboration. However, their effectiveness is limited as they originally have no RE purpose and typically are restricted to their members. Latest RE approaches close this gap and also apply motivation strategies, which, however, are simplified, missing the high heterogeneity of stakeholders out- side organizational reach; thus, risking to demotivate them. This thesis presents the GARUSO (Game-based Requirements Elicitation) approach, a novel RE approach specifically designed for stakeholders outside organizational reach. It provides (1) a strategy to identify them and (2) a social media based platform that enables their collaborative participation in RE and applies gamification to motivate them to do so. The GARUSO platform is the core of the thesis. Its conceptual solution is inspired by the structure of user stories, the experiential learning theory, motivational psychology and game design. As a proof of concept, it was implemented to elicit and prioritize requirements and evaluated in a field study with promising results: The identified stakeholders build a highly heterogeneous crowd which participated - over a period of three months - in platform activities. They perceived the platform easy to understand, interesting to use and during their participation increased their knowledge on the application domain of the software system of interest.
Simone Porru, Andrea Pinna, Michele Marchesi, Roberto Tonelli
The Blockchain technology is reshaping finance, economy, money to the extent that its disruptive power is compared to that of the Internet and the Web in their early days. As a result, all the software development revolving around the Blockchain technology is growing at a staggering rate. In this paper, we acknowledge the need for software engineers to devise specialized tools and techniques for blockchain-oriented software development. From current challenges concerning the definition of new professional roles, demanding testing activities and novel tools for software architecture, we take a step forward by proposing new directions on the basis of a curate corpus of blockchain-oriented software repositories, detected by exploiting the information enclosed in the 2016 Moody's Blockchain Report and teh market capitalization of cryptocurrencies. Ensuring effective testing activities, enhancing collaboration in large teams, and facilitating the development of smart contracts all appear as key factors in the future of blockchain-oriented software development.
The rapid development of the blockchain technology and its various applications has rendered it important to understand the guidelines for adopting it. The comparative analysis method is used to analyze different dimensions of the maturity model, which is mainly based on the commonly used capability maturity model. The blockchain maturity model and its adoption process have been discussed and presented. This study serves as a guide to institutions to make blockchain adoption decisions more systematically.