Test Case Generation with Hecate: To Infinity and Beyond!

Test Case Generation with Hecate: To Infinity and Beyond! | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Test Case Generation with Hecate: To Infinity and Beyond! Nunzio Marco Bisceglia, Michael Marzella, Daniele Lazzari, Marcello Minervini, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9160890/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Developing dependable cyber-physical systems often requires engineers to uncover software defects. Search-based software testing (SBST) is a wellestablished approach to support this activity, yet broader industrial uptake calls for solid empirical evidence across multiple benchmarks and application domains. In this replication study, we report our experience evaluating SBST for generating failure-revealing test cases on two representative controllers: the software controller of an electric-bike (e-Bike) motor and the software controller of an autonomous drone executing line-following tasks. For the e-Bike controller, we replicate our prior ssessment of Hecate, an SBST framework for Simulink® models, and analyze its effectiveness and efficiency. For the drone controller, we extend the evaluation by comparing Hecate with S-TaLiRo using the same set of requirements and testing budget. The results indicate that SBST can expose failures within practical time limits in both domains, while the comparison also sheds light on differences in failure-discovery capability and search efficiency between the two tools. We present our lessons learned, discuss implications for industrial adoption, and outline how these findings can help advance current practice. Motor Control E-Bikes Autonomous Drones Model Development Simulink® Search-based Software Testing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 06 May, 2026 Reviewers agreed at journal 27 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviewers invited by journal 06 Apr, 2026 Editor assigned by journal 22 Mar, 2026 Submission checks completed at journal 19 Mar, 2026 First submitted to journal 18 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9160890","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":621575461,"identity":"dd77ccd9-178a-4454-a49b-666d8efa8230","order_by":0,"name":"Nunzio Marco Bisceglia","email":"","orcid":"","institution":"Gran Sasso Science Institute","correspondingAuthor":false,"prefix":"","firstName":"Nunzio","middleName":"Marco","lastName":"Bisceglia","suffix":""},{"id":621575462,"identity":"de69406a-cd11-4614-9400-60f795ac7505","order_by":1,"name":"Michael Marzella","email":"","orcid":"","institution":"University of 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