The C++ programming language remains widely used, despite inheriting many unsafe features from C-features that often lead to failures of type or memory safety that manifest as buffer overflows, use-after-free vulnerabilities, or abstraction violations. Malicious attackers can exploit such violations to compromise application and system security.This paper introduces Ironclad C++, an approach to bringing the benefits of type and memory safety to C++. Ironclad C++ is, in essence, a library-augmented, type-safe subset of C++. All Ironclad C++ programs are valid C++ programs that can be compiled using standard, off-the-shelf C++ compilers. However, not all valid C++ programs are valid Ironclad C++ programs: a syntactic source-code validator statically prevents the use of unsafe C++ features. To enforce safety properties that are difficult to check statically, Ironclad C++ applies dynamic checks via templated "smart pointer" classes.Using a semi-automatic refactoring tool, we have ported nearly 50K lines of code to Ironclad C++. These benchmarks incur a performance overhead of 12% on average, compared to the original unsafe C++ code.

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Correctly synchronizing multithreaded programs is challenging and errors can lead to program failures such as atomicity violations. Existing strong memory consistency models rule out some possible failures, but are limited by depending on programmer-defined locking code. We present the new Ordering-Free Region (OFR) serializability consistency model that ensures atomicity for OFRs, which are spans of dynamic instructions between consecutive ordering constructs (e.g., barriers), without breaking atomicity at lock operations. Our platform, Serializable Ordering-Free Regions for Increasing Thread Atomicity Scalably (SOFRITAS), ensures a C/C++ program's execution is equivalent to a serialization of OFRs by default. We build two systems that realize the SOFRI-TAS idea: a concurrency bug finding tool for testing called SofriTest, and a production runtime system called SoPro.SofriTest uses OFRs to find concurrency bugs, including a multi-critical-section atomicity violation in memcached that weaker consistency models will miss. If OFRs are too coarse-grained, SofriTest suggests refinement annotations automatically. Our software-only SoPro implementation has high performance, scales well with increased parallelism, and prevents failures despite bugs in locking code. SoPro has an average overhead of just 1.59x on a single-threaded execution and 1.51x on sixteen threads, despite pthreads' much weaker memory model.

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Enabling programmers to write correct and efficient parallel code remains an important challenge, and the prevalence of on-chip accelerators exacerbates this challenge. Novice programmers, especially those in disciplines outside of Computer Science and Computer Engineering, need to be able to write code that exploits parallelism and heterogeneity, but the frameworks for writing parallel and heterogeneous programs expect expert knowledge and experience. More effort must be put into understanding how novice programmers solve parallel problems. Unfortunately, novice programmers are difficult to study because they are, by definition, novices. We have designed a visual programming language and game-based framework for studying how novice programmers solve parallel problems. This tool was used to conduct an initial study on 95 undergraduate students with little to no prior programming experience. 71% of all volunteer participants completed the study in 48 minutes on average. This study demonstrated that novice programmers could solve parallel problems, and this framework can be used to conduct more thorough studies of how novice programmers approach parallel code.