Probabilistic thread algebra

We add probabilistic features to basic thread algebra and its extensions with thread-service interaction and strategic interleaving. Here, threads represent the behaviours produced by instruction sequences under execution and services represent the behaviours exhibited by the components of execution environments of instruction sequences. In a paper concerned with probabilistic instruction sequences, we proposed several kinds of probabilistic instructions and gave an informal explanation for each of them. The probabilistic features added to the extension of basic thread algebra with thread-service interaction make it possible to give a formal explanation in terms of non-probabilistic instructions and probabilistic services. The probabilistic features added to the extensions of basic thread algebra with strategic interleaving make it possible to cover strategies corresponding to probabilistic scheduling algorithms.Comment: 25 pages (arXiv admin note: text overlap with arXiv:1408.2955, arXiv:1402.4950); some simplifications made; substantially revise

Turing Impossibility Properties for Stack Machine Programming

The strong, intermediate, and weak Turing impossibility properties are introduced. Some facts concerning Turing impossibility for stack machine programming are trivially adapted from previous work. Several intriguing questions are raised about the Turing impossibility properties concerning different method interfaces for stack machine programming.Comment: arXiv admin note: substantial text overlap with arXiv:0910.556

Metamorphic Code Generation from LLVM IR Bytecode

Metamorphic software changes its internal structure across generations with its functionality remaining unchanged. Metamorphism has been employed by malware writers as a means of evading signature detection and other advanced detection strate- gies. However, code morphing also has potential security benefits, since it increases the “genetic diversity” of software. In this research, we have created a metamorphic code generator within the LLVM compiler framework. LLVM is a three-phase compiler that supports multiple source languages and target architectures. It uses a common intermediate representation (IR) bytecode in its optimizer. Consequently, any supported high-level programming language can be transformed to this IR bytecode as part of the LLVM compila- tion process. Our metamorphic generator functions at the IR bytecode level, which provides many advantages over previously developed metamorphic generators. The morphing techniques that we employ include dead code insertion—where the dead code is actually executed within the morphed code—and subroutine permutation. We have tested the effectiveness of our code morphing using hidden Markov model analysis

About Decisiveness of Dynamic Probabilistic Models

Decisiveness of infinite Markov chains with respect to some (finite or infinite) target set of states is a key property that allows to compute the reachability probability of this set up to an arbitrary precision. Most of the existing works assume constant weights for defining the probability of a transition in the considered models. However numerous probabilistic modelings require the (dynamic) weight to also depend on the current state. So we introduce a dynamic probabilistic version of counter machine (pCM). After establishing that decisiveness is undecidable for pCMs even with constant weights, we study the decidability of decisiveness for subclasses of pCM. We show that, without restrictions on dynamic weights, decisiveness is undecidable with a single state and single counter pCM. On the contrary with polynomial weights, decisiveness becomes decidable for single counter pCMs under mild conditions. Then we show that decisiveness of probabilistic Petri nets (pPNs) with polynomial weights is undecidable even when the target set is upward-closed unlike the case of constant weights. Finally we prove that the standard subclass of pPNs with a regular language is decisive with respect to a finite set whatever the kind of weights

About Instruction Sequence Testing

Software testing is presented as a so-called theme within which different authors and groups have defined different subjects each of these subjects having a different focus on testing. A uniform concept of software testing is non-existent and the space of possible coherent perspectives on software testing, each fitting within the theme, is viewed as being spanned by five dimensions, each dimension representing two opposite views with a variety of intermediate views in between. Instruction sequences are used as a simple theoretical conceptualization of computer programs. A theory of instruction sequence testing may serve as a model for a theory of software testing. Instruction sequences testing is considered a new topic for which definitions may be freely contemplated without being restricted by existing views on software testing. The problem of developing a theory of instruction sequence testing is posed. A survey is given of motivations and scenarios for developing a theory of instruction sequence testing

Indirect jumps improve instruction sequence performance

Instruction sequences with direct and indirect jump instructions are as expressive as instruction sequences with direct jump instructions only. We show that, in the case where the number of instructions is not bounded, we are faced with increases of the maximal internal delays of instruction sequences on execution that are not bounded by a linear function if we strive for acceptable increases of the lengths of instruction sequences on elimination of indirect jump instructions.Comment: 10 pages, definition of maximal internal delay and theorem 1 are stated more precise; presentation improve