Improving quality, efficiency, software trustworthiness
Our research in software development spans all aspects of making developers more productive and software more trustworthy. It includes programming-language design, compilers, specification and verification, development environments and tools, runtime environments, formal models of systems, performance monitoring and optimization, security and privacy, software analytics, and quality improvement.
We work on tools, languages, and methodologies to increase dramatically the productivity of software development. We are interested in analysis tools for existing software and in asking questions about how the software of the future should be designed and developed.
Abram Hindle, Christian Bird, Thomas Zimmermann, and Nachiappan Nagappan, Do Topics Make Sense to Managers and Developers?, in Empirical Software Engineering, Springer, December 2015.
Emerson Murphy-Hill, Thomas Zimmermann, Christian Bird, and Nachiappan Nagappan, The Design Space of Bug Fixes and How Developers Navigate It, in IEEE Transactions on Software Engineering, IEEE – Institute of Electrical and Electronics Engineers, December 2015.
Pantazis Deligiannis, Jeroen Ketema, Paul Thomson, Alastair Donaldson, and Akash Lal, Asynchronous Programming, Analysis and Testing with State Machines, in Programming Language Design and Implementation (PLDI), ACM, June 2015.
Akash Lal and Shaz Qadeer, Deciding Reachability in Hierarchical Programs Using DAG Inlining, in Programming Language Design and Implementation (PLDI), ACM, June 2015.
Edward K. Smith, Christian Bird, and Thomas Zimmermann, Build it yourself! Homegrown tools in a large software company, in Proceedings of the 37th International Conference on Software Engineering, IEEE – Institute of Electrical and Electronics Engineers, May 2015.
- T2 Temporal Prover
- Sampling software projects
- Tark: A Tool Kit to Mine Linear Temporal Rules
- Code Hunt Community
- Code Hunt
- Ziria - Wireless Programming for Hardware Dummies
- Live Programming
- Logging practice study
- Code Completion
- Contextual Fuzzing for Mobile App Testing
- The R2 Project
- Neural Networks for Software Developers
- Q Program Verifier
- T2 temporal prover
- Code Digger
- Automated Problem Generation for Education