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Samurai - Protecting Critical Data in Unsafe Languages

Samurai - Protecting Critical Data in Unsafe Languages. Karthik Pattabiraman, Vinod Grover, Benjamin G. Zorn.

Programs written in type-unsafe languages such as C and C++ incur costly memory errors that result in corrupted data structures, program crashes, and incorrect results. We present a data-centric solution to memory corruption called critical memory, a memory model that allows programmers to identify and protect data that is critical for correct program execution. Critical memory defines operations to consistently read and update critical data, and ensures that other non-critical updates in the program will not corrupt it. We also present Samurai, a runtime system that implements critical memory in software. Samurai uses replication and forward error correction to provide probabilistic guarantees of critical memory semantics. Because Samurai does not modify memory operations on non-critical data, the majority of memory operations in programs run at full speed, and Samurai is compatible with third party libraries. Using both applications, including a Web server, and libraries (an STL list class and a memory allocator), we evaluate the performance overhead and fault tolerance that Samurai provides.

An acceptable overhead for the pleasure of using an unsafe language? You decide.

Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach

Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach
Emanuel Kitzelmann, Ute Schmid; JMLR Volume 7(Feb), 2006.

We describe an approach to the inductive synthesis of recursive equations from input/output-examples which is based on the classical two-step approach to induction of functional Lisp programs of Summers (1977). In a first step, I/O-examples are rewritten to traces which explain the outputs given the respective inputs based on a datatype theory. These traces can be integrated into one conditional expression which represents a non-recursive program. In a second step, this initial program term is generalized into recursive equations by searching for syntactical regularities in the term. Our approach extends the classical work in several aspects. The most important extensions are that we are able to induce a set of recursive equations in one synthesizing step, the equations may contain more than one recursive call, and additionally needed parameters are automatically introduced.

Is this the future of programming?