This paper presents a general approach to annotation inference for a given static program checker. The approach reuses the checker as a subroutine. The approach has been used to implement annotation inference systems for two static program checkers, ESC/Java and rccjava. The paper describes

This paper presents a general approach to annotation inference for a given static program checker. The approach reuses the checker as a subroutine. The approach has been used to implement annotation inference systems for two static program checkers, ESC/Java and rccjava. The paper describes

A modular static program checker relies on annotations specifying module interfaces. Writing annotations is a burden to the programmer. The Houdini algorithm is a whole-program analysis that reduces this burden by inferring many annotations automatically. The basic

Automated code generation is an enabling technology for

the code to be verified to be heavily annotated. In this paper, we attempt to combine the best of both worlds by starting off with a manual verification tool based on separation logic for which we develop techniques to automatically generate part of the required annotations. This approach provides more

). Here we describe a new generic post-generation annotation inference algorithm that circumvents these problems. We exploit the fact that the output of a code generator is highly idiomatic, so that patterns can be used to describe all code constructs that require annotations. The patterns are specific

). Here we describe a new generic post-generation annotation inference algorithm that circumvents these problems. We exploit the fact that the output of a code generator is highly idiomatic, so that patterns can be used to describe all code constructs that require annotations. The patterns are specific

restrictive for practical use and have not been implemented. In this paper, we describe the new language JFlow, an extension to the Java language that adds statically-checked information flow annotations. JFlow provides several new features that make information flow checking more flexible and convenient than

unique aspects: it does not require the programmer to annotate the source program (invariants are inferred); it minimizes noise (false error messages) through a process known as "counterexample-driven refinement". SLAM exploits and extends results fi'om program analysis, model checking

We present a system for extending standard type systems with flow-sensitive type qualifiers. Users annotate their programs with type qualifiers, and inference checks that the annotations are correct. In our system only the type qualifiers are modeled flow-sensitively - the underlying standard types