Iulian Neamtiu
New Jersey Institute of Technology, NJ·Computer Science
Many everyday programs, such as phone apps, websites and smart-home devices, are built around events: taps, network messages or sensor readings that the underlying platform delivers to the program at times the program does not control. Because the platform, not the code, decides when events fire, these event-based systems are hard to reason about and prone to bugs.
- Fields
Computer Science
Engineering
- Topics
static analysis
program analysis
event-based systems
- Grants
- 1 known grant, last ended Sep 2026
What they work on
- Develop event sensitivity, a program-analysis technique that treats event creation and triggering as first-class objects, so that static analysis can model event-based applications accurately.
- Build path-based event ordering analyses that determine, before a program runs, the order of key events in Android, JavaScript and IoT programs, so that ordering errors can be prevented.
- Create static reasoning about event-induced volatility to detect state loss and state inconsistency, errors that occur when the platform destroys or changes program state unexpectedly.
- Automatically construct models of how platforms such as Android generate and deliver events, replacing current manual or ad hoc models, for use in analysis and program understanding.
More about the research
Users may lose their work in a mobile app, a Web service may fail silently or go down, and an Internet-of-Things (IoT) device may behave unexpectedly.
Why it matters
Mobile apps, Web services and IoT devices are used by billions of people, and event-ordering bugs in them can lose users' data, cause outages or make devices misbehave. Analysis tools that catch these errors before software ships could help Android, JavaScript and IoT developers build more reliable applications. The automatically built platform models may also help programmers understand how existing apps behave.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Zhijia Zhao
University of California-Riverside, CA·Computer Science
Develop 'event sensitivity', a program-analysis foundation that treats event creation and triggering as first-class objects, so that static analysis can track event-based Android, JavaScript and IoT programs.
Shiyi Wei
University of Texas at Dallas, TX·Computer Science·Early-career
Identify hidden relationships among the configuration options of Android taint analysis tools, and present them in a unified, configuration-aware interface that makes tuning easier.
Qirun Zhang
Georgia Institute of Technology, GA·Computer Science·Early-career
Characterize what the InterDyck graph abstraction can and cannot express. This is a graph model of programs with matched-edge patterns that represents program meaning for analysis.
The school
New Jersey Institute of Technology: 12 labs on PI Pages, $172M a year on research, 74 research doctorates a year.
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