Software Debug Research Articles

A Semi-parametric NHPP-based Software Reliability Modeling with Local Polynomial Debug Rate

In this paper, we propose a new non-homogeneous Poisson process (NHPP) based software reliability model (SRM), where the software debug rate is given by a local polynomial function. The main feature of this semi-parametric SRM is to control the goodness-of-fit by changing the polynomial degree. Numerical examples with 16 actual software development project data are devoted to comparing our SRM with the well-known existing NHPP-based SRMs in terms of goodness-of-fit and predictive performances.

The Design of Positioning Terminal Based on NEO-5Q

This paper introduces a design of liquid crystal GPS positioning terminal based on microcontroller, the system consists of a GPS module, 12864 liquid crystal display module, MCU minimum system module, power module. The paper mainly puts forward the scheme and software design idea, hardware design and debug, the extraction system can realize the positioning and navigation information parameters of GPS global positioning system and the information parameters is analyzed.

A Soft Computing Approach to Crack Detection and Impact Source Identification with Field-Programmable Gate Array Implementation

The real-time nondestructive testing (NDT) for crack detection and impact source identification (CDISI) has attracted the researchers from diverse areas. This is apparent from the current work in the literature. CDISI has usually been performed by visual assessment of waveforms generated by a standard data acquisition system. In this paper we suggest an automation of CDISI for metal armor plates using a soft computing approach by developing a fuzzy inference system to effectively deal with this problem. It is also advantageous to develop a chip that can contribute towards real time CDISI. The objective of this paper is to report on efforts to develop an automated CDISI procedure and to formulate a technique such that the proposed method can be easily implemented on a chip. The CDISI fuzzy inference system is developed using MATLAB’s fuzzy logic toolbox. A VLSI circuit for CDISI is developed on basis of fuzzy logic model using Verilog, a hardware description language (HDL). The Xilinx ISE WebPACK9.1i is used for design, synthesis, implementation, and verification. The CDISI field-programmable gate array (FPGA) implementation is done using Xilinx’s Spartan 3 FPGA. SynaptiCAD’s Verilog Simulators—VeriLogger PRO and ModelSim—are used as the software simulation and debug environment.

Automated software attack recovery using rollback and huddle

While research into building robust and survivable networks has steadily intensified in recent years, similar efforts at the application level and below have focused primarily on attack discovery, ignoring the larger issue of how to gracefully recover from an intrusion at that level. Our work attempts to bridge this inherent gap between theory and practice through the introduction of a new architectural technique, which we call rollback and huddle. Inspired by concepts made popular in the world of software debug, we propose the inclusion of extra on-chip hardware for the efficient storage and tracing of execution contexts. Upon the detection of some software protection violation, the application is restarted at the last known safe checkpoint (the rollback part). During this deterministic replay, an additional hw/sw module is then loaded that can increase the level of system monitoring, log more detailed information about any future attack source, and potentially institute a live patch of the vulnerable part of the software executable (the huddle part). Our experimental results show that this approach could have a practical impact on modern computing system architectures, by allowing for the inclusion of low-overhead software security features while at the same time incorporating an ability to gracefully recover from attack.

Quasi-Random Testing

Our paper proposes an implementable procedure for using the method of quasi-random sequences in software debug testing. In random testing, the sequence of tests (if considered as points in an -dimensional unit hypercube) will give rise to regions where there are clusters of points, as well as underpopulated regions. Quasi-random sequences, also known as low-discrepancy or low-dispersion sequences, are sequences of points in such a hypercube that are spread more evenly throughout. Based on the observation that program faults tend to lead to contiguous failure regions within a program's input domain, and that an even spread of random tests enhances the failure detection effectiveness for certain failure patterns, we examine the use of quasi-random sequences as a replacement for random sequences in automated testing. Because there are only a small number of quasi-random sequence generation algorithms, and each of them can only generate a small number of distinct sequences, the applicability of quasi-random sequences in testing real programs is severely restricted. To alleviate this problem, we examine the use of two types of randomized quasi-random sequences, which are quasi-random sequences permuted in a nondeterministic fashion in such a way as to retain their low discrepancy properties. We show that testing using randomized quasi-random sequences is often significantly more effective than random testing.