Previous work has shown that early resolution of issues detected by static code analyzers can prevent major costs later on. However, developers often ignore such issues for two main reasons. First, many issues should be interpreted to determine if they correspond to actual flaws in the program. Second, static analyzers often do not present the issues in a way that is actionable. To address these problems, we present Sorald: a novel system that uses metaprogramming templates to transform the abstract syntax trees of programs and suggests fixes for static analysis warnings. Thus, the burden on the developer is reduced from interpreting and fixing static issues, to inspecting and approving full fledged solutions. Sorald fixes violations of 10 rules from SonarJava, one of the most widely used static analyzers for Java. We evaluate Sorald on a dataset of 161 popular repositories on Github. Our analysis shows the effectiveness of Sorald as it fixes 65% (852/1,307) of the violations that meets the repair preconditions. Overall, our experiments show it is possible to automatically fix notable violations of the static analysis rules produced by the state-of-the-art static analyzer SonarJava.

We show that only languages in BPP have public-coin black-box zero-knowledge protocols that are secure under an unbounded (polynomial) number of parallel repetitions. This result holds both in the plain model (without any setup) and in the bare public key model (where the prover and the verifier have registered public keys). We complement this result by constructing a public-coin black-box zero-knowledge proof based on one-way functions that remains secure under any a priori bounded number of concurrent executions. A key step (of independent interest) in the analysis of our lower bound shows that any public-coin protocol, when repeated sufficiently in parallel, satisfies a notion of “resettable soundness” if the verifier picks its random coins using a pseudorandom function.