Simulated Software Testing Process and Its Optimization Considering Heterogeneous Debuggers and Release Time

Abstract

Most traditional software reliability growth models (SRGMs) assume immediate fault correction upon detection and therefore only consider fault detection process (FDP). In order to be more realistic, some researchers have tried to incorporate fault correction process (FCP) and fault introduction process (FIP) into the software reliability models. However, it is still difficult to incorporate into the analytical software reliability models some other factors, such as the different fault detection and correction capabilities of debuggers. In this paper, a simulation approach is proposed to model FDP, FIP, and FCP together considering debuggers with different contributions to fault detection rate, different fault correction rate and different fault introduction rate. Besides, this paper also constructed a cost calculation method to optimize the testing design including debuggers assignment and software release time. Some numerical examples are provided to illustrate the proposed model. The results show that the trends of FDP, FCP and FIP are consistent with the intuition to the practice of software testing, and the optimal testing resources allocation and the optimal release time can be obtained according to the proposed model.

Extending the Space of Software Test Monitoring: Practical Experience

“…In many papers testing is correlated with software reliability. Software reliability growth models (SRGMs) are proposed to predict bugs in software, needed testing time to achieve an assumed quality level (release time), optimization of resources and test costs ( [7] [11] and references therein). On the other hand, diverse publications focus on specific test problems: test algorithms based on structural, functional, and mixed approaches, test efficiency, software quality, etc.…”

“…The heat map for alert types revealed bigger number of some critical types: unavailable sender (187 and 146 for log11 and 12, respectively), SenderCriticalError (533-2045 for logs [13][14][15], AccountJobinactive (555-1405 for logs 11 and 10), transactioBad Message (218-251 for logs 1-3), securityviolation (200-604 for logs 18,11,12), transactionResponseTimeout (100-604 for logs 13). Five logs did not comprise alerts, for 4 logs alerts constituted a fraction of percent, 3 logs with about 2-5%, the remaining ones below 2%.…”

Multi-State System Reliability Evaluation and Component Allocation Optimization Under Multi-Level Performance Sharing

“…0,5 [1,3] 0,5 [1,4] 0,5 0,0 [1,5] ( ) 0.6324 ( ) 0.258 0.59925 ( ) 0.729 ( ) 0.5445 ( ) 0.4965 0.0153 7) Probability distribution of deficient and surplus performance of the second layer subsystem…”

“…Under this development trend, various engineering systems have gradually become huge and complex, showing the characteristics of multi-state and performance sharing, especially in power, communication, computer, intelligent transportation and other systems abound with high techniques [1][2][3][4][5][6]. As these systems play a vital role in the stable operation and development of society and economy, once the system fails, it may cause major economic losses and disastrous consequences that affect society [7][8][9]. Therefore, the research on the reliability of multi-state system with performance sharing has received extensive attention from scholars.…”

Optimal interception strategy of air defence missile system considering multiple targets and phases

“…For example, attackers usually launch multiple offensive weapons at one time and each of these weapons is a target that needs to be intercepted. The working process of many modern systems needs several phases, [32][33][34][35][36][37][38] especially some complex systems. [39][40][41] For example, the flight of Intercontinental ballistic missile (ICBM) after launching can be divided into three stages: propulsion and acceleration stage, midway stage and re-entry stage, which gives three phases to intercept ICBM.…”