Automatic discovery of relationships among values of array elements is a challenging problem due to the unbounded nature of arrays. We present a framework for analyzing array operations that is capable of capturing numeric properties of array elements.In particular, the analysis is able to establish that all array elements are initialized by an array-initialization loop, as well as to discover numeric constraints on the values of initialized elements.The analysis is based on the combination of canonical abstraction and summarizing numeric domains. We describe a prototype implementation of the analysis and discuss our experience with applying the prototype to several examples, including the verification of correctness of an insertion-sort procedure.
The goal of this work is to develop compile-time algorithms for automatically verifying properties of imperative programs that manipulate dynamically allocated storage. The paper presents an analysis method that uses a characterization of a procedure's behavior in which parts of the heap not relevant to the procedure are ignored. The paper has two main parts: The first part introduces a non-standard concrete semantics, LSL, in which called procedures are only passed parts of the heap. In this semantics, objects are treated specially when they separate the "local heap" that can be mutated by a procedure from the rest of the heap, which-from the viewpoint of that procedure-is non-accessible and immutable. The second part concerns abstract interpretation of LSL and develops a new static-analysis algorithm using canonical abstraction.
We address the problem of testing atomicity of composed concurrent operations. Concurrent libraries help programmers exploit parallel hardware by providing scalable concurrent operations with the illusion that each operation is executed atomically. However, client code often needs to compose atomic operations in such a way that the resulting composite operation is also atomic while preserving scalability. We present a novel technique for testing the atomicity of client code composing scalable concurrent operations. The challenge in testing this kind of client code is that a bug may occur very rarely and only on a particular interleaving with a specific thread configuration. Our technique is based on modular testing of client code in the presence of an adversarial environment; we use commutativity specifications to drastically reduce the number of executions explored to detect a bug. We implemented our approach in a tool called COLT, and evaluated its effectiveness on a range of 51 real-world concurrent Java programs. Using COLT, we found 56 atomicity violations in Apache Tomcat, Cassandra, MyFaces Trinidad, and other applications.
We describe an abstract interpretation based framework for proving relationships between sizes of memory partitions. Instances of this framework can prove traditional properties such as memory safety and program termination but can also establish upper bounds on usage of dynamically allocated memory. Our framework also stands out in its ability to prove properties of programs manipulating both heap and arrays which is considered a difficult task. Technically, we define an abstract domain that is parameterized by an abstract domain for tracking memory partitions (sets of memory locations) and by a numerical abstract domain for tracking relationships between cardinalities of the partitions. We describe algorithms to construct the transfer functions for the abstract domain in terms of the corresponding transfer functions of the parameterized abstract domains. A prototype of the framework was implemented and used to prove interesting properties of realistic programs, including programs that could not have been automatically analyzed before.
Linearizable libraries provide operations that appear to execute atomically. Clients, however, may need to execute a sequence of operations (a composite operation) atomically. We consider the problem of extending a linearizable library to support arbitrary atomic composite operations by clients. We introduce a novel approach in which the concurrent library ensures atomicity of composite operations by exploiting information (foresight) provided by its clients. We use a correctness condition, based on a notion of dynamic rightmovers, that guarantees that composite operations execute atomically without deadlocks, and without using rollbacks.We present a static analysis to infer the foresight information required by our approach, allowing a compiler to automatically insert the foresight information into the client. This relieves the client programmer of this burden and simplifies writing client code.We present a generic technique for extending the library implementation to realize foresight-based synchronization. This technique is used to implement a general-purpose Java library for Map data structures -the library permits composite operations to simultaneously work with multiple instances of Map data structures.We use the Maps library and the static analysis to enforce atomicity of a wide selection of real-life Java composite operations. Our experiments indicate that our approach enables realizing efficient and scalable synchronization for real-life composite operations.
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