Application of decision tree to selection of MTBM for adverse geological conditions

So many potential risks can be identifed for application of trenchless technology especially using microtunneling methods.Unexpected changes in ground conditions,such as encountering boulders,tree roots,ground water and man-made structures such as old foundations are the principal geotechnical risks,which affect the selection of an appropriate microtunnel boring machine.On the other hand,the performance of each microtunneling technique will differ while encountering such conditions.Hence,predicting the potential hazards provides a better safety and risk management plan.In this study,a couple of potentially hazardous situation,which are commonly associated with ground conditions,were identifed and investigated.A decision tree aid methodology was proposed based on geotechnical risk assessment for selection of proper microtunneling technique.Based on the approach the most appropriate microtunneling technique has the minimum risk level either before or after hazards mitigation measures.In order to check the effciency of the approach in practice,selection of microtunnel boring machine for Hamadan sewerage pipeline project was evaluated.Accordingly,an earth pressure balance(EPB)MTBM was selected for the project.

MEASURING C PROGRAM COVERAGE BASED ON BINARY DECISION DIAGRAMS

Test coverage analysis is a structural testing technique, which helps to evaluate the sufficiency of software testing. This letter presents two test generation algorithms based on binary decision diagrams to produce tests for the Multiple-Condition Criterion(M-CC) and the Modified Condition/Decision Criterion(MC/DC), and describes the design of the C program Coverage Measurement Tool (CCMT), which can record dynamic behaviors of C programs and quantify test coverage.

Modified condition/decision coverage(MC/DC)oriented compiler optimization for symbolic execution

Symbolic execution is an effective way of systematically exploring the search space of a program,and is often used for automatic software testing and bug finding.The program to be analyzed is usually compiled into a binary or an intermediate representation,on which symbolic execution is carried out.During this process,compiler optimizations influence the effectiveness and efficiency of symbolic execution.However,to the best of our knowledge,there exists no work on compiler optimization recommendation for symbolic execution with respect to(w.r.t.)modified condition/decision coverage(MC/DC),which is an important testing coverage criterion widely used for mission-critical software.This study describes our use of a state-of-the-art symbolic execution tool to carry out extensive experiments to study the impact of compiler optimizations on symbolic execution w.r.t.MC/DC.The results indicate that instruction combining(IC)optimization is the important and dominant optimization for symbolic execution w.r.t.MC/DC.We designed and implemented a support vector machine based optimization recommendation method w.r.t.IC(denoted as auto).The experiments on two standard benchmarks(Coreutils and NECLA)showed that auto achieves the best MC/DC on 67.47%of Coreutils programs and 78.26%of NECLA programs.

Reliability Analysis of Aircraft Condition Monitoring Network Using an Enhanced BDD Algorithm

The aircraft condition monitoring network is responsible for collecting the status of each component in aircraft. The reliability of this network has a significant effect on safety of the aircraft. The aircraft condition monitoring network works in a real-time manner that all the data should be transmitted within the deadline to ensure that the control center makes proper decision in time. Only the connectedness between the source node and destination cannot guarantee the data to be transmitted in time. In this paper, we take the time deadline into account and build the task-based reliability model. The binary decision diagram （BDD）, which has the merit of efficiency in computing and storage space, is introduced when calculating the reliability of the network and addressing the essential variable. A case is analyzed using the algorithm proposed in this paper. The experimental results show that our method is efficient and proper for the reliability analysis of the real-time network.