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Safe, Secure and Smart Software (S3) Lab


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  Mission
 
The overarching goal of our research is to make computing systems more reliable and automatic. We apply program analysis, synthesis and machine learning techniques to automatically build reliable and secure computing systems. We are broadly interested in both formal methods, and concurrent and distributed computing.

Prospective Students

 
  People


PI:
   Mohsen Lesani

Students:
   Jeremiah Griffin
  
Farzin Hooshmand
   Narges Shadab
   Xizhe Yin


  Recent Publications


Replication Coordination Analysis and Synthesis
Farzin Hooshmand, Mohsen Lesani
Accepted with revisions to POPL'19 (ACM Principles of Programming Languages)
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BioScript: Programming Safe Chemistry of Laboratories-on-a-Chip
Jason Ott, Chris Curtis, Tyson Loveless, Mohsen Lesani, Philip Brisk
OOPSLA'18 (ACM Object-oriented Programming, Systems, Languages, and Applications)
Distinguished paper award
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The rest of publications


  Projects


Distributed Systems

Replication Coordination Analysis and Synthesis
Replicated systems are widely deployed to tolerate faults in aviation control systems and geo-distributed data stores. Given high-level sequential specifications, we automatically analyze the specifications and synthesize consistent, convergent and coordination-avoiding replicated distributed systems.
See the POPL'19 paper.

Certified Key-value Stores
We implement, specify and mechanically verify distributed key-value stores in proof assistants.
See the POPL'16 paper.

Ongoing project: Compositional Verification of Distributed System Stacks
What are the fundamental principles for compositional verification of distributed systems? We design program logics and compositional verification techniques to build certified distributed system stacks.
See our NSF-supported project.

Ongoing: Automatic Synthesis of Parallel and Distributed Graph-processing Programs
Given a high-level specification of a graph processing problem, we automatically synthesize programs for multiple parallel and distributed graph-processing frameworks.

Blockchains and Cryptocurrencies

Ongoing project: Efficient Blockchain Protocols
Proof-of-work protocol wastes a huge amount of computational power. What are more energy-efficient blockchain protocols?

Ongoing project: Certified Blockchains with Explicit Safety and Security Guarantees
What are the correctness conditions and verification principles for blockchain protocols? We aim at building certified blockchains with explicit safety and security guarantees using proof assistants.

Concurrent Systems

Transaction Specification, Testing and Verification
What are the correctness criteria and proof techniques for transactions?
See the DISC'14 paper, WTTM'12 and WTTM'13 papers.
We presented a testing technique that found bugs in transaction algorithms.
See the DISC'13 paper.
We have built a mechanically checked framework for verification of transactional memory algorithms.
See the CONCUR'12 paper.
We specify and implement safe transactions in the presence of communication between them.
See the PPoPP'12 paper.

Verification of Concurrent Data Structures
Composing atomic concurrent operations is challenging and researchers have found a myriad of atomicity bugs in compositions of concurrent libraries. We automatically verify the atomicity of compositions.
See the CAV'14 paper.

Automatic Fence Insertion
To gain performance, compilers and processors reorder program instructions. Reordering instructions may violate safety of concurrent executions. Experts insert fence instructions to prevent violating reorders. We automate fence insertion.
See the OOPSLA'15 paper and PODC'17 paper.

Ongoing: Certified Composable Concurrent Programming
We are building a certified concurrent collections library that supports atomic composition of method calls across objects.

Trust and Security

Ongoing: Memory safety
Malicious attackers can use out-of-bound memory accesses to take over the whole system. We develop static and dynamic techniques to ensure that memory accesses are within bounds and within the access capabilities of the enclosing module.
See our NSF-supported project.

Static Analysis for Secure Cloud Computations
To protect user privacy, we encrypt data before processing it in the cloud. We apply type inference to find the most efficient encryption scheme.
See the OOPSLA'13 paper.

Trust Aggregation and Inference in Social Networks
Given local trust information between direct friends, we automatically infer a trust measure between any pair of users.
See the JCI'09 paper

Machine Learning

Ongoing Project: Robust Machine Learning
Reliable deployment of machine learning in mission- and life-critical applications requires the specification and verification of their safety and security properties. What are the specification and verification methods for reliability of learned models? Can we devise training algorithms with reliability guarantees or verify learned models?

Learning Performance Models to Guide Synthesis of Efficient Concurrent Data Structures
Given a high-level relational specification of data, we want to automatically synthesize efficient concurrent data structures. Performance is an irregular phenomenon that can be only learned from experiments. We train neural networks as performance models. We use the performance model to choose the most efficient candidate from the space of possible candidate data structures.

Cooperation between Q-Learning Agents
We presented a technique for cooperation between heterogeneous Q-learning agents.
See the SMC'04 paper.

Programmable Biochemistry

Language and Type System for Programming Biochemistry
We introduce the BioScript domain-specific language for programmable biochemistry which executes on emerging microfluidic platforms and the ChemType type system that ensures that the chemical interactions are safe.
See the OOPSLA'18 paper.

Ongoing: Drug Synthesis
Can we apply program synthesis techniques to automatically synthesize drugs with specified properties?


  Sponsors


NSF SHF CRII: Certified Byzantine Fault-tolerant Systems. Mohsen Lesani. 2017-2019
NSF SaTC: Practical Whole Kernel Memory Safety Enforcement. Chengyu Song, Mohsen Lesani. 2017-2020