NHPP Testability Growth Model Considering Testability Growth Effort, Rectifying Delay, and Imperfect Correction

Tianmei Li,Hong Pei,Zonghao Yang,Yuzhe Ma,Xiaosheng Si

doi:10.1109/access.2019.2962528

Tianmei Li, Hong Pei + Show 3 more

Open Access

https://doi.org/10.1109/access.2019.2962528

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 18	License type: CC BY 4.0

Affiliation: Xi'an High Tech University

Abstract

Over the last several years, many testability growth models (TGMs) have been developed to greatly facilitate engineers and managers in tracking and measuring the growth of testability as system is being improved. Most TGMs consider only one or two variation patterns of the aspects, such as the testability growth effort (TGE) in testability design limitation (TDL) identification, the rectifying delay and the new TDL introduction in TDL correction. However, the ignorance of such joint consideration may lead to a lower fitting ability to the fault detection/isolation data. Inspired by the counting idea of non-homogeneous Poisson process (NHPP), a NHPP based testability growth model (TGM) considering the recurrence rate function (RRF) of TDL identification, TDL correction and new TDL introduction is proposed for the foundation of TGM. A real data set of a missile control system is used to validate the above TGMs in fitting ability, estimation accuracy and prediction capability. Results show that the bell-shaped curve can fit the identification process and rectifying delay process of TDL well, and the imperfect correction of TDL really exists in the testability growth test (TGT), and the inflected s-shaped and Gamma function based TGM gives good capacity to the real data set.

Highlights

Testability is defined as the probability of fault detection and isolation, which is quantified by various testability indexes, such as fault detection rate (FDR), fault isolation rate, fault alarm rate, and so on [1]–[3]
Referring the ideas of software growth models, we propose a testability growth models (TGMs) considering the testability growth effort, rectifying delay and imperfect correction simultaneously based on nonhomogeneous Poisson process (NHPP)
This paper uses the above some bell-shaped curves to describe the relationship between the test time and the amount of testability growth effort (TGE) expended during that time by analyzing the consumption rule of TGE so as to obtain the identification rate of testability design limitation (TDL)

Summary

INTRODUCTION

Testability is defined as the probability of fault detection and isolation, which is quantified by various testability indexes, such as fault detection rate (FDR), fault isolation rate, fault alarm rate, and so on [1]–[3]. The identification rate of TDLs depends on the testability growth effort consumed on TGT, and the correction rate of TDLs and the introduction rate of new TDLs depends on the level of designers which is time-varying with the learning process of testability designer. Together with these discussions, it is concluded that how to jointly consider TDL identification, TDL correction and new TDL introduction to propose TGM is a very important problem. This paper proposes a new NHPP TGM to jointly consider the testability growth effort, rectifying delay, and imperfect correction. Referring the ideas of software growth models, we propose a TGM considering the testability growth effort, rectifying delay and imperfect correction simultaneously based on NHPP.

NHPP IN TDL IDENTIFICATION

NHPP IN NEW TDLs INTRODUCTION

CASE STUDY

CONCLUSION