C to O-O Translation: Beyond the Easy Stuff

Can we reuse some of the huge code-base developed in C to take advantage of modern programming language features such as type safety, object-orientation, and contracts? This paper presents a source-to-source translation of C code into Eiffel, a modern object-oriented programming language, and the supporting tool C2Eif. The translation is completely automatic and supports the entire C language (ANSI, as well as many GNU C Compiler extensions, through CIL) as used in practice, including its usage of native system libraries and inlined assembly code. Our experiments show that C2Eif can handle C applications and libraries of significant size (such as vim and libgsl), as well as challenging benchmarks such as the GCC torture tests. The produced Eiffel code is functionally equivalent to the original C code, and takes advantage of some of Eiffel's object-oriented features to produce safe and easy-to-debug translations

Structural Analysis: Shape Information via Points-To Computation

This paper introduces a new hybrid memory analysis, Structural Analysis, which combines an expressive shape analysis style abstract domain with efficient and simple points-to style transfer functions. Using data from empirical studies on the runtime heap structures and the programmatic idioms used in modern object-oriented languages we construct a heap analysis with the following characteristics: (1) it can express a rich set of structural, shape, and sharing properties which are not provided by a classic points-to analysis and that are useful for optimization and error detection applications (2) it uses efficient, weakly-updating, set-based transfer functions which enable the analysis to be more robust and scalable than a shape analysis and (3) it can be used as the basis for a scalable interprocedural analysis that produces precise results in practice. The analysis has been implemented for .Net bytecode and using this implementation we evaluate both the runtime cost and the precision of the results on a number of well known benchmarks and real world programs. Our experimental evaluations show that the domain defined in this paper is capable of precisely expressing the majority of the connectivity, shape, and sharing properties that occur in practice and, despite the use of weak updates, the static analysis is able to precisely approximate the ideal results. The analysis is capable of analyzing large real-world programs (over 30K bytecodes) in less than 65 seconds and using less than 130MB of memory. In summary this work presents a new type of memory analysis that advances the state of the art with respect to expressive power, precision, and scalability and represents a new area of study on the relationships between and combination of concepts from shape and points-to analyses

Size-Change Termination as a Contract

Termination is an important but undecidable program property, which has led to a large body of work on static methods for conservatively predicting or enforcing termination. One such method is the size-change termination approach of Lee, Jones, and Ben-Amram, which operates in two phases: (1) abstract programs into "size-change graphs," and (2) check these graphs for the size-change property: the existence of paths that lead to infinite decreasing sequences. We transpose these two phases with an operational semantics that accounts for the run-time enforcement of the size-change property, postponing (or entirely avoiding) program abstraction. This choice has two key consequences: (1) size-change termination can be checked at run-time and (2) termination can be rephrased as a safety property analyzed using existing methods for systematic abstraction. We formulate run-time size-change checks as contracts in the style of Findler and Felleisen. The result compliments existing contracts that enforce partial correctness specifications to obtain contracts for total correctness. Our approach combines the robustness of the size-change principle for termination with the precise information available at run-time. It has tunable overhead and can check for nontermination without the conservativeness necessary in static checking. To obtain a sound and computable termination analysis, we apply existing abstract interpretation techniques directly to the operational semantics, avoiding the need for custom abstractions for termination. The resulting analyzer is competitive with with existing, purpose-built analyzers

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

HardScope: Thwarting DOP with Hardware-assisted Run-time Scope Enforcement

Widespread use of memory unsafe programming languages (e.g., C and C++) leaves many systems vulnerable to memory corruption attacks. A variety of defenses have been proposed to mitigate attacks that exploit memory errors to hijack the control flow of the code at run-time, e.g., (fine-grained) randomization or Control Flow Integrity. However, recent work on data-oriented programming (DOP) demonstrated highly expressive (Turing-complete) attacks, even in the presence of these state-of-the-art defenses. Although multiple real-world DOP attacks have been demonstrated, no efficient defenses are yet available. We propose run-time scope enforcement (RSE), a novel approach designed to efficiently mitigate all currently known DOP attacks by enforcing compile-time memory safety constraints (e.g., variable visibility rules) at run-time. We present HardScope, a proof-of-concept implementation of hardware-assisted RSE for the new RISC-V open instruction set architecture. We discuss our systematic empirical evaluation of HardScope which demonstrates that it can mitigate all currently known DOP attacks, and has a real-world performance overhead of 3.2% in embedded benchmarks