Concurrent programming errors arise when threads share data incorrectly. Programmers often avoid these errors by using synchronization to enforce a simple ownership policy: data is either owned exclusively by a thread that can read or write the data, or it is read owned by a set of threads that can read but not write the data. Unfortunately, incorrect synchronization often fails to enforce these policies and memory errors in languages like C and C++ can violate these policies even when synchronization is correct. In this paper, we present a dynamic analysis for checking ownership policies in concurrent C and C++ programs despite memory errors. The analysis can be used to find errors in commodity multi-threaded programs and to prevent attacks that exploit these errors. We require programmers to write ownership assertions that describe the sharing policies used by different parts of the program. These policies may change over time, as may the policies' means of enforcement, whether it be locks, barriers, thread joins, etc. Our compiler inserts checks in the program that signal an error if these policies are violated at runtime. We evaluated our tool on several benchmark programs. The run-time overhead was reasonable: between 0 and 49% with an average of 26%. We also found the tool easy to use: the total number of ownership assertions is small, and the asserted specification and implementation can be debugged together by running the instrumented program and addressing the errors that arise. Our approach enjoys a pleasing modular soundness property: if a thread executes a sequence of statements on variables it owns, the statements are serializable within a valid execution, and thus their effects can be reasoned about in isolation from other threads in the program.
Safe programming languages are readily available, but many applications continue to be written in unsafe languages because of efficiency. As a consequence, many applications continue to have exploitable memory safety bugs. Since garbage collection is a major source of inefficiency in the implementation of safe languages, replacing it with safe manual memory management would be an important step towards solving this problem. Previous approaches to safe manual memory management use programming models based on regions, unique pointers, borrowing of references, and ownership types. We propose a much simpler programming model that does not require any of these concepts. Starting from the design of an imperative type safe language (like Java or C#), we just add a delete operator to free memory explicitly and an exception which is thrown if the program dereferences a pointer to freed memory. We propose an efficient implementation of this programming model that guarantees type safety. Experimental results from our implementation based on the C# native compiler show that this design achieves up to 3x reduction in peak working set and run time.
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