The PNZ software reliability model revisited

Other Title(s)

إعادة النظر في نموذج (PNZ)‎ لعول البرمجيات

Dissertant

Idris, Khalid Hasan Muhammad

Thesis advisor

Shatnawi, Umar Ali

Comitee Members

al-Smadi, Adnan M.
Battayihah, Khalid
Shatnawi, Raid

University

Al albayt University

Faculty

Prince Hussein Bin Abdullah Faculty for Information Technology

Department

Department of Computer Science

University Country

Jordan

Degree

Master

Degree Date

2009

English Abstract

In the present scenario, computer systems are indispensable for society and their need and importance are increasing rapidly.

To meet this increasing demand, the complexity of the software products to construct such computer systems, has enhanced to a considerable extent.

During the development of such complex software systems, many software failures may occur.

To reduce these faults, thorough testing of the software is required so that a highly reliable software system can be developed.

Over the past three decades, there have been several attempts at modeling the processes associated with software failures based on various underlying assumptions related to how software is tested.

These models are collectively known as software reliability growth model (SRGMs).

It is important to note that due to the complexity of software design, it is not expected that any single model can incorporate all factors which are thought to influence software reliability.

In this thesis, we show how beginning with very simple assumptions, non-homogenous Poisson process (NHPP) type of continuous time SRGM, are gradually made more realistic with the incorporation of imperfect debugging, involvement of a learning-process in debugging and introduction of new faults.

The applicability of the resultant generalized model is demonstrated through several actual software reliability data sets obtained from different software development projects.

The proposed generalized model is also checked against different components of the model, including existing one (e.g., PNZ, Inflection S-shaped, Fault Generation, Imperfect, Delayed S-shaped, Exponential) thus highlighting its applicability.

The software reliability data sets were deliberately chosen from different testing environments where the growth curves ranging from purely exponential to highly S-shaped.

The results are fairly encouraging in terms of goodness of fit, predictive validity and software reliability evaluation measures.

The major contribution of this thesis is its introduction the concept of two types of imperfect debugging during software fault removal phenomenon with logistic fault removal rate.

Most of the SRGMs discussed in the literature seldom differentiate between the failure observation and fault removal processes.

In real software development environment, the number of failures observed need not be same as the number of fault removed.

If the number of failures observed is more than the number of faults removed then we have the case of imperfect debugging.

Due to the complexity of the software system and the incomplete understanding of the software requirements, specifications and structure, the testing team may not be able to remove the fault perfectly on the detection of the failure and the original fault may remain or get replaced by another fault.

While the first phenomenon is known as imperfect debugging, the second is called fault generation.

In case of imperfect debugging the fault-content of the software is not changed, but just because of incomplete understanding of the software, the detected fault is not removed completely.

But in case of fault generation the fault-content increases as the testing progresses and removal results in introduction of new faults while removing old ones.

To model learning, fault removal rate has been taken as logistic function.

Actual software reliability data cited from real software development projects have been used to demonstrate the applicability of the proposed model.

The results of the proposed model are encouraging in terms of goodness of fit criteria, predictive validity criterion, and software reliability evaluation measures for software reliability data due to its applicability and flexibility.

Main Subjects

Information Technology and Computer Science

No. of Pages

59

Table of Contents

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Language

English

Data Type

Arab Theses

Record ID

BIM-314903