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Portrait of Valerio Terragni

The Luvo 100 / ANZ

69No. 69 of the
Luvo 100 ANZ
↑ 17

Valerio Terragni

Senior Lecturer
University of Auckland
New Zealand

Testing Research & Education

Why Valerio Terragni is in the Luvo 100

Valerio co-authored research applying differential testing — comparing results from the same tests across different software versions — to software-supply-chain integrity. The study examined 3,541 pairs of builds, with results and reproduction tools made openly available for researchers and engineers to examine and reuse. This work explores how automated tests can expose behavioural differences that could signal compromised software or runtime failures.

About

Valerio Terragni is a Senior Lecturer at the University of Auckland, developing automated software-testing techniques to generate test cases and assess system behaviour when expected outputs are difficult to specify. Beyond core testing methodologies, research areas span software-supply-chain integrity and AI systems. Before moving to Auckland, Valerio worked as a Senior Research Fellow at USI Università della Svizzera italiana in Switzerland, following a PhD completed at the Hong Kong University of Science and Technology in 2017.

Valerio co-authored Towards Cross-Build Differential Testing, investigating whether programs built from the same source code behave differently across builds. The study evaluated 3,541 pairs of binaries using EvoSuite to generate tests automatically, demonstrating how cross-build differential testing can reveal behavioural discrepancies that may indicate compromised software or runtime failures. An accompanying open dataset provides results and reproduction tools, allowing researchers and engineers to scrutinise the findings and build on the approach.

Career highlights

  • Senior Lecturer at the University of Auckland
  • Previously a Senior Research Fellow at USI Università della Svizzera italiana in Switzerland
  • Completed a PhD at the Hong Kong University of Science and Technology in 2017
  • Co-authored Towards Cross-Build Differential Testing, cited for ICST 2025
  • Released an open dataset and reproduction tools analysing 3,541 pairs of software builds