CiFi: Versatile Analysis of Class and Field Immutability

Abstract

This paper was accepted in 2021 at the 36th IEEE/ACM International Conference on Automated Software Engineering and proposes a model for immutability analysis. Reasoning about immutability is important for preventing bugs, e.g., in multi-threaded software. Static analysis to infer immutability properties has mostly focused on individual objects and references. Reasoning about fields and entire classes, while significantly simpler, has gained less attention. A consistently used terminology is missing, which makes it difficult to implement analyses that rely on immutability information. We propose a model for class and field immutability that unifies terminology for immutability flavors considered by previous work and covers new levels of immutability to handle lazy initialization and immutability dependent on generic type parameters. Using the OPAL static analysis framework, we implement CiFi, a set of modular, collaborating analyses for different flavors of immutability, inferring the properties defined in our model. We propose a benchmark of representative test cases for class and field immutability. We use the benchmark to showcase CiFi's precision and recall in comparison to state of the art and use CiFi to study the prevalence of immutability in real-world libraries, showcasing the practical quality and relevance of our model.