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

Teaching Common Japanese Cultural Practices Online

Many university students in Hawaii planning to study abroad in Japan will experience some form of cultural miscommunication and misunderstanding. These experiences can make it difficult for students to join authentic Japanese communities during their time abroad. To help solve this issue, this project designed and evaluated online asynchronous instruction about common Japanese cultural practices. The instruction combined multimedia with various interactive activities to help students 1) be more aware of the cultural differences between their home culture and Japanese culture and 2) make adjustments so they can participate in the Japanese community more easily. The instruction used Bloom’s Taxonomy to break down and sequence the content, as well as Gagne’s Nine Events of Instruction and Keller’s ARCS model to ensure the lessons targeted the cognitive and affective domains. To evaluate the instruction, synchronous usability testing and asynchronous learning effectiveness testing were conducted with 16 Japanese language learning students (n = 16). The usability test helped capture diverse perspectives on the design of the instruction and was valuable in revising its navigation. In general, participants felt the instructional lessons were meaningful and enjoyable. Future work will be needed to research more about the target audience and to include more content covering additional cultural practices

A Comparison of Computer Aided Instruction Versus Traditional Instruction in an Elementary Algebra Course

The purpose of this study was to compare and evaluate the effectiveness of computer assisted instruction versus traditional laboratory instruction for educating freshman college students (n=174) about elementary algebra.  The study treated computer testing and tutorial simulated instruction and traditional instruction as independent variables and learning outcome and attitude, based on posttest scores, as the dependent variables.  The findings indicated that sequence of the both methods of instructions was a significant factor.  Students learned more mathematical concepts when they utilized the traditional method of instruction and then used computer laboratory instruction (MyMthLab)

Putting Instruction Sequences into Effect

An attempt is made to define the concept of execution of an instruction sequence. It is found to be a special case of directly putting into effect of an instruction sequence. Directly putting into effect of an instruction sequences comprises interpretation as well as execution. Directly putting into effect is a special case of putting into effect with other special cases classified as indirectly putting into effect

Towards Smart Hybrid Fuzzing for Smart Contracts

Smart contracts are Turing-complete programs that are executed across a blockchain network. Unlike traditional programs, once deployed they cannot be modified. As smart contracts become more popular and carry more value, they become more of an interesting target for attackers. In recent years, smart contracts suffered major exploits, costing millions of dollars, due to programming errors. As a result, a variety of tools for detecting bugs has been proposed. However, majority of these tools often yield many false positives due to over-approximation or poor code coverage due to complex path constraints. Fuzzing or fuzz testing is a popular and effective software testing technique. However, traditional fuzzers tend to be more effective towards finding shallow bugs and less effective in finding bugs that lie deeper in the execution. In this work, we present CONFUZZIUS, a hybrid fuzzer that combines evolutionary fuzzing with constraint solving in order to execute more code and find more bugs in smart contracts. Evolutionary fuzzing is used to exercise shallow parts of a smart contract, while constraint solving is used to generate inputs which satisfy complex conditions that prevent the evolutionary fuzzing from exploring deeper paths. Moreover, we use data dependency analysis to efficiently generate sequences of transactions, that create specific contract states in which bugs may be hidden. We evaluate the effectiveness of our fuzzing strategy, by comparing CONFUZZIUS with state-of-the-art symbolic execution tools and fuzzers. Our evaluation shows that our hybrid fuzzing approach produces significantly better results than state-of-the-art symbolic execution tools and fuzzers

Software-Based Self-Test of Set-Associative Cache Memories

Embedded microprocessor cache memories suffer from limited observability and controllability creating problems during in-system tests. This paper presents a procedure to transform traditional march tests into software-based self-test programs for set-associative cache memories with LRU replacement. Among all the different cache blocks in a microprocessor, testing instruction caches represents a major challenge due to limitations in two areas: 1) test patterns which must be composed of valid instruction opcodes and 2) test result observability: the results can only be observed through the results of executed instructions. For these reasons, the proposed methodology will concentrate on the implementation of test programs for instruction caches. The main contribution of this work lies in the possibility of applying state-of-the-art memory test algorithms to embedded cache memories without introducing any hardware or performance overheads and guaranteeing the detection of typical faults arising in nanometer CMOS technologie

Neural Machine Translation Inspired Binary Code Similarity Comparison beyond Function Pairs

Binary code analysis allows analyzing binary code without having access to the corresponding source code. A binary, after disassembly, is expressed in an assembly language. This inspires us to approach binary analysis by leveraging ideas and techniques from Natural Language Processing (NLP), a rich area focused on processing text of various natural languages. We notice that binary code analysis and NLP share a lot of analogical topics, such as semantics extraction, summarization, and classification. This work utilizes these ideas to address two important code similarity comparison problems. (I) Given a pair of basic blocks for different instruction set architectures (ISAs), determining whether their semantics is similar or not; and (II) given a piece of code of interest, determining if it is contained in another piece of assembly code for a different ISA. The solutions to these two problems have many applications, such as cross-architecture vulnerability discovery and code plagiarism detection. We implement a prototype system INNEREYE and perform a comprehensive evaluation. A comparison between our approach and existing approaches to Problem I shows that our system outperforms them in terms of accuracy, efficiency and scalability. And the case studies utilizing the system demonstrate that our solution to Problem II is effective. Moreover, this research showcases how to apply ideas and techniques from NLP to large-scale binary code analysis.Comment: Accepted by Network and Distributed Systems Security (NDSS) Symposium 201