Faults prediction using object-oriented software metric /

Recently, the Open Source Software (OSS) has gained popularity and has impacted the software industry at large. Many agencies, including the Malaysian government agencies are adopting open source projects due to the merit they offer. Due to the vast usage of OSS in the government administrations and...

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主要作者: Nadiah binti Arsat
格式: Thesis
語言:English
出版: Gombak, Selangor : Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 2016
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在線閱讀:http://studentrepo.iium.edu.my/handle/123456789/5398
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040 |a UIAM  |b eng 
041 |a eng 
043 |a a-my--- 
050 0 0 |a QA76.76.S46 
100 1 |a Nadiah binti Arsat 
245 1 |a Faults prediction using object-oriented software metric /  |c by Nadiah binti Arsat 
260 |a Gombak, Selangor : Kulliyyah of Information and Communication Technology, International Islamic University Malaysia,   |c 2016 
300 |a xiv, 96 leaves :  |b ill. ;  |c 30cm. 
502 |a Thesis (MCS)--International Islamic University Malaysia, 2016. 
504 |a Includes bibliographical references (leaves 83-92) 
520 |a Recently, the Open Source Software (OSS) has gained popularity and has impacted the software industry at large. Many agencies, including the Malaysian government agencies are adopting open source projects due to the merit they offer. Due to the vast usage of OSS in the government administrations and many reported problems, there is a pivotal need to study on reliability and quality of the code for those applications. Thus, the attribute of the source code of these applications should be measured. This research investigates how the object-oriented metrics by Chidamber and Kemerer (CK) are used to predict the fault-proneness in the source code of the open source applications used by the Malaysian government, namely, MyMeeting, MyTaskManager and MyBooking. In this research, in order to validate the usefulness of object-oriented metrics for fault-proneness prediction, several analyses are conducted using Statistical Package for Social Sciences (SPSS) such as Spearman correlation, multiple linear regressions and univariate logistic regression and a mathematical model is develop to study its relationship with faults. The results show that only Depth of Inheritance Tree (DIT) metrics is useful in fault-proneness prediction in the open source applications. 
596 |a 1 
655 |a Theses, IIUM local 
690 |a Dissertations, Academic  |x Department of Computer Science  |z IIUM 
710 |a International Islamic University Malaysia.  |b Department of Computer Science 
856 |u http://studentrepo.iium.edu.my/handle/123456789/5398 
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