Systems & Pl
better programming for better systems building

Writing correct programs is the foundation of building reliable software systems. Programming language designers constantly seeks new approaches to improve the efficiency, relability, and flexibility of software programming. However, less is known about how effective these new approaches are in the real world. We take an empirical view of new programming languages features by studying real-world usages and issues (i.e., bugs) and by building tools that can help programmers avoid or detect bugs.



Empirical Study on Rust Safety Bugs

Rust is a young programming language designed for systems software development. It aims to provide safety guarantees like high-level languages and performance efficiency like low-level languages. The core design of Rust is a set of strict safety rules enforced by compile-time checking. To support more low-level controls, Rust allows programmers to bypass these compiler checks to write unsafe code.

It is important to understand what safety issues exist in real Rust programs and how Rust safety mechanisms impact programming practices. We performed the first empirical study of Rust by close, manual inspection of 850 unsafe code usages and 170 bugs in five open-source Rust projects, five widely-used Rust libraries, two online security databases, and the Rust standard library. Our study answers three important questions: how and why do programmers write unsafe code, what memory-safety issues real Rust programs have, and what concurrency bugs Rust programmers make. Our study reveals interesting real-world Rust program behaviors and new issues Rust programmers make.


Empirical Study on Go Concurrency Bugs

Go is a statically-typed programming language that aims to provide a simple, efficient, and safe way to build multithreaded software. Since its creation in 2009, Go has matured and gained significant adoption in production and open-source software. Go advocates for the usage of message passing as the means of inter-thread communication and provides several new concurrency mechanisms and libraries to ease multi-threading programming. It is important to understand the implication of these new proposals and the comparison of message passing and shared memory synchronization in terms of program errors, or bugs. Unfortunately, as far as we know, there has been no study on Go’s concurrency bugs.

We performed the first systematic study on concurrency bugs in real Go programs. We studied six popular Go software including Docker, Kubernetes, and gRPC. We analyzed 171 concurrency bugs in total, with more than half of them caused by non-traditional, Go-specific problems. Our study provides a better understanding on Go’s concurrency models and can guide future researchers and practitioners in writing better, more reliable Go software and in developing debugging and diagnosis tools for Go.

Related Publication


Conferences and Journals

Understanding Real-World Concurrency Bugs in Go
Tengfei Tu, Xiaoyu Liu, Linhai Song, Yiying Zhang
Proceedings of the 24th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '19)