This vision paper presents a workflow that operationalizes constantly evolving regulatory requirements into automated developer-focused tests and orchestration of requirements elicitation, regulatory interpretation, traceability, test generation, and developer feedback into a continuous compliance workflow.
C. Brandt, S. Abualhaija· Proceedings of the 41st IEEE...· 0 citations
Fuzzing is a highly effective automated testing method for uncovering software vulnerabilities. Despite advances in fuzzing techniques, many fuzzers still struggle with coverage plateaus caused by fuzz blockers, which limit their ability to discover deeper vulnerabilities. We introduce InsightQL, the first human-assist...
Wen-Tao Gao, Renata Borovica-Gajic, Sang Kil Cha et al.· Proceedings of the 41st IEEE...· 0 citations
This work developed an LLM-assisted automated discriminatory test generation approach for identifying discriminatory behavior in ML model outcomes using GPT-4o Mini and Claude Sonnet 4 model and shows that LLM-assisted approach achieves higher success rates in identifying discriminatory behavior compared to existing st...
Sadia Afrin Mim, F. Zohra, Brittany Johnson· 0 citations
The findings indicate that industry measurement remains largely tool-driven, emphasizing artifact properties that can be readily automated, and more holistic assessments will require practitioners and researchers to develop and validate complementary measures of people and practices.
Alexis Butler, Dan O'Keeffe, Santanu Kumar Dash· Proceedings of the 2nd Inter...· 0 citations
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This paper presents a compact, low-polarization-dependent-loss (PDL) O-band coarse wavelength division multiplexing (CWDM) silicon photonic receiver utilizing active coherent combining. To overcome the substantial footprint of conventional polarization-diversity circuits and mitigate dynamic signal fading in practical...
Li-Yong Guo, Song Huang, Han-Ming Yang et al.· Journal of Lightwave Technol...· 0 citations
An LLM-driven testing framework that reformulates accessibility evaluation into an automated reachability problem and effectively uncovers four types of dynamic accessibility defects: non-interactive control, navigation trap, improper focus ordering, and navigation dead zone is presented.
A systematic evaluation of the capability of large language models (LLMs) in new feature implementation, with a task setup strictly aligned with real-world software development practices, shows that new feature implementation of LLMs adhering to real-world world software development practices remains challenges.
J. Li, Ting-Xuan Huang, Tian Zhao et al.· Proceedings of the 41st IEEE...· 0 citations
The results show that CoCoS supports the conservative bounding of regression scopes while preserving compliance-oriented reasoning and providing practical evidence for test planning in safety-critical environments.
Francesco Basciani, Daniele Masti, Patrizio Pelliccione et al.· Proceedings of the 41st IEEE...· 0 citations
The design enables continuous execution of large certification test suites while preserving reproducibility, traceability, and result analysis and features a multi-runner model that enables efficient on-commit execution of hundreds of certification test sequences.
Jacopo Maltagliati, Salvatore De Simone, G. Denaro· 0 citations
This work presents the first formalisation of testability for quantum programs, adapting classical concepts to quantum computation by introducing Quantum Squeeziness, an information-theoretic metric inspired by classical squeeziness to quantify how faults are masked and prevented from propagating to observable outcomes...
Avner Bensoussan, H. Menéndez, Mohammad Reza Mousavi· 1 citation
It is found that LLM-based approaches can generate incorrect, overspecified, or incomplete test suites in all configurations, and that the configuration has less of an effect on the generated tests than expected.
Sarah Dagger· Proceedings of the 41st IEEE...· 0 citations
“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
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