Research on Software Defects Predict Methods Based on Bayesian Network = Research on Software Defects Predict Methods Based on Bayesian Network

다국어 초록 (Multilingual Abstract)

Software defect prediction is an important process in software quality management process. To get Acquire of which files/modules are most likely to contain the largest numbers of defects always in a large software system have significant values to any project developers. For a large scale software system development, testing is also a hard work. Software defect prediction technique gives testers a guide to design the test process, of which file/module are probably to present failures when running or which file/module would include the most density of defects.
To accomplish this, in this thesis, we first review past papers to under software defect prediction technique, then analysis software design metrics, which are deem to efficiently predict software quality in the early age of software development, then analysis these metrics through a Bayesian Network method. The probability computation based on Bayesian has a strong theory basis and is concise to compute and easy to understand. In this model how to choose factors can thin and thick on the basis of taking into account technique and management status of team, it can choose data flexible according as expert experience.
During software development it is helpful to obtain early estimates of the defect density of software components. Such estimates identify fault-prone areas of code requiring further testing.

목차 (Table of Contents)

• 1 Introduction 1
• 1.1 Motivation 1
• 1.2 Acronyms and terminology 2
• 1.3 Outline 4
• 2 Background 5
• 2.1 Terminologies related with software defects 5
• 2.2 Related work 7
• 3 Software Code Metrics 12
• 4 Predict Software Failure-prone with Bayesian Network 16
• 4.1 Bayesian Network: An Overview 16
• 4.2 Model Construction 20
• 5 Experiment 24
• 5.1 Extracting Information 25
• 5.2 Performance Assessment 26
• 6 Conclusions 29
• 7 REFERENCES 30