We present an integrated proof language for guiding the actions of multiple reasoning systems as they work together to prove complex correctness properties of imperative programs. The language operates in the context of a program verification system that uses multiple reasoning systems to discharge generated proof obligations. It is designed to 1) enable developers to resolve key choice points in complex program correctness proofs, thereby enabling automated reasoning systems to successfully prove the desired correctness properties; 2) allow developers to identify key lemmas for the reasoning systems to prove, thereby guiding the reasoning systems to find an effective proof decomposition; 3) enable multiple reasoning systems to work together productively to prove a single correctness property by providing a mechanism that developers can use to divide the property into lemmas, each of which is suitable for a different reasoning system; and 4) enable developers to identify specific lemmas that the reasoning systems should use when attempting to prove other lemmas or correctness properties, thereby appropriately confining the search space so that the reasoning systems can find a proof in an acceptable amount of time.

The Jahob program verification system leverages state of the art automated theorem provers, shape analysis, and decision procedures to check that programs conform to their specifications. By combining a rich specification language with a diverse collection of verification technologies, Jahob makes it possible to verify complex properties of programs that manipulate linked data structures. We present our results using Jahob to achieve full functional verification of a collection of linked data structures.

We present the first verification of full functional correctness for a range of linked data structure implementations, including mutable lists, trees, graphs, and hash tables. Specifically, we present the use of the Jahob verification system to verify formal specifications, written in classical higher-order logic, that completely capture the desired behavior of the Java data structure implementations (with the exception of properties involving execution time and/or memory consumption). Given that the desired correctness properties include intractable constructs such as quantifiers, transitive closure, and lambda abstraction, it is a challenge to successfully prove the generated verification conditions.

Hob is a program analysis system that enables the focused application of multiple analyses to different modules in the same program. In our approach, each module encapsulates one or more data structures and uses membership in abstract sets to characterize how objects participate in data structures. Each analysis verifies that the implementation of the module 1) preserves important internal data structure consistency properties and 2) correctly implements a set algebra interface that characterizes the effects of operations on the data structure. Collectively, the analyses use the set algebra to 1) characterize how objects participate in multiple data structures and to 2) enable the interanalysis communication required to verify properties that depend on multiple modules analyzed by different analyses. We implemented our system and deployed several pluggable analyses, including a flag analysis plug-in for modules in which abstract set membership is determined by a flag field in each object, a PALE shape analysis plug-in, and a theorem proving plug-in for analyzing arbitrarily complicated data structures. Our experience shows that our system can effectively 1) verify the consistency of data structures encapsulated within a single module and 2) combine analysis results from different analysis plug-ins to verify properties involving objects shared by multiple modules analyzed by different analyses

We present a new analysis for removing unnecessary write barriers in programs that use generational garbage collection. To our knowledge, this is the first static program analysis for this purpose. Our algorithm uses a pointer analysis to locate assignments that always create a reference from a younger object to an older object, then transforms the program to remove the write barriers normally associated with such assignments. We have implemented two transformations that reorder object allocations; these transformations can significantly increase the effectiveness of our write barrier removal algorithm.Our base technique assumes that the collector promotes objects in age order. We have developed an extension that enables the optimistic removal of write barriers, with the collector lazily adding each newly promoted object into a remembered set of objects whenever the compiler may have removed write barriers involving the object at statements that have yet to execute. This mechanism enables the application of our technique to virtually any memory management system that uses write barriers to enable generational garbage collection.Results from our implemented system show that our technique can remove substantial numbers of write barriers from the majority of the programs in our benchmark set, producing modest performance improvements of up to 6% of the overall execution time. Moreover, by dynamically instrumenting the executable, we are able to show that for six of our nine benchmark programs, our analysis is close to optimal in the sense that it removes the write barriers for almost all assignments that do not, in the observed execution, create a reference from an older object to a younger object. Finally, our results show that the overhead of our optimistic extension is negligible.