Joong-Yang Park

A Class of Discrete Time Coverage Growth Functions for Software Reliability Engineering

Coverage-based NHPP SRGMs have been introduced in order to incorporate the coverage growth behavior into the NHPP SRGMs. The coverage growth function representing the coverage growth behavior during testing is thus an essential factor of the coverage-based NHPP SRGMs. This paper proposes a class of discrete time coverage growth functions and illustrates its application to real data sets.

Evaluation and Application of MVFs in Coverage for Coverage-Based NHPP SRGM Frameworks

Many non-homogeneous Poisson process software reliability growth models are characterized by their mean value functions. Mean value functions of coverage-based models are usually obtained as composite functions of the coverage growth function and the function relating the number of detected faults to the coverage. This paper performs empirical evaluation of the relationships between the number of detected faults and the coverage embedded in the coverage- based software reliability growth models. It is also illustrated that integration of well-performing coverage growth functions and relationships between the number of detected faults and the coverage produces well-performing mean value functions.

INTEGRATION OF IMPERFECT DEBUGGING IN GENERAL TESTING-DOMAIN DEPENDENT NHPP SRGM

Recently the general testing-domain dependent NHPP SRGM is developed to reflect repeated execution of constructs and location of detected faults. It assumes that debugging is perfect. Since realistic models need to reflect imperfect debugging, this paper integrates imperfect debugging in the general testing-domain dependent NHPP SRGM. Differential equations representing the mean value function are first derived for general testing strategy and then realized for the uniform testing. Specific mean value functions are obtained for some selected fault detection rate functions and constant fault reduction rate. Finally empirical performance evaluation is fulfilled.

A Coverage-Based Software Reliability Growth Model for Imperfect Fault Detection and Repeated Construct Execution

Recently relationships between reliability measures and the coverage have been developed for evaluation of software reliability. Particularly the mean value function of the coverage-based software reliability growth model is important because of its key role in rep-resenting the software reliability growth. In this paper, we first review the problems of the existing mean value functions with respect to the assumptions on which they are based. Then a new mean value function is proposed. The new mean value function is developed for a general testing environment in which imperfect fault detection and repeated construct execution are allowed. Finally performance of the proposed model is empirically evaluated by applying it to a real data set.

Program Slicing in the Presence of Complicated Data Structure

Program slicing is s method to extract the statements from the program which have an influence on the value of a variable at a paricular point of the program. Program slicing is applied for many applications, such as program degugging, program testing, program integration, parallel program execution, software metrics, reverse engineering, and software maintenance, etc. This paper is the study to create the exact slice in the presence of Object Reference State Graph to generate more exactly static analysis information of objects in the program of the presence of complicated data structure.