Using consensus to automatically infer post-conditions

Abstract

Formal behavioral specifications help ensure the correctness of programs. Writing such specifications by hand however is time-consuming and requires substantial expertise. Previous studies have shown how to use a notion of consensus to automatically infer pre-conditions for APIs by using a large set of projects. In this work, we propose a similar idea of consensus to automatically infer post-conditions for popular APIs. We propose two new algorithms for mining potential post-conditions from API client code. The first algorithm looks for guarded post-conditions that test the value returned from the API and throws an exception. The second algorithm looks for values flowing from the API to another API with already known preconditions, which recommends them as post-conditions of the first API.