Prediction of fault-prone modules provides one way to support software quality engineering through improved scheduling and project control. There are many metrics and techniques available to investigate the accuracy of fault prone classes which may help software organizations for planning and performing testing activities. Bayes algorithms are being successfully applied for solving both classif...

In any manufacturing environment, the fault introduction rate might be considered one of the most meaningful criterion to evaluate the goodness of the development process. In many investigations, the estimates of such a rate are often oversimplified or misunderstood generating unrealistic expectations on the prediction power of regression models with a fault criterion. The computation of fault ...

In Computer Science, an emulator is hardware or software or both that duplicates (or emulates) the functions of one computer system (the guest) in another computer system (the host), different from the first one, so that the emulated behavior closely resembles the behavior of the real system (the guest). The computer systems are an affected by software and hardware fault, solved in numerous mec...

In Computer Science, an emulator is hardware or software or both that duplicates (or emulates) the functions of one computer system (the guest) in another computer system (the host), different from the first one, so that the emulated behavior closely resembles the behavior of the real system (the guest).The computer systems are an affected by software and hardware fault, solved in numerous mech...

Different distance measures have been used for efficiently predicting software faults at early stages of software development. One stereotyped approach for software fault prediction due to its computational efficiency is K-means clustering, which partitions the dataset into K number of clusters using any distance measure. Distance measures by using some metrics are used to extract similar data ...

Software metrics play an important role in measuring the quality of software. It is desirable to predict the quality of software as early as possible, and hence metrics have to be collected early as well. This raises a number of questions that has not been fully answered. In this paper we discuss, prediction of fault content and try to answer what type of metrics should be collected, to what ex...

In dynamic software development, organize the optimization of the usage of resources in order to deliver the product within the finite time is an essential and computational challenging task. Certain robust methods are required to fulfill the requirement of the users to prevent or repair the software faults especially object communications when they are required to inherit in diverse natures. I...

Empirical validation of software metrics suites to predict fault proneness in object-oriented (OO) components is essential to ensure their accuracy in practical industrial. In this paper, we empirically validate the Chidamber and Kemerer (CK) metrics suite metrics for their ability to predict software quality in terms of fault-proneness: we explore the ability of these metrics suites to predict...

Complexity is an important quality attribute. Software complexity can be measured in design phase may produce good quality product.In this paper,we measure the complexity of object-oriented system at design phase to predict the fault-prone classes.The facility to predict the fault-prone classes can provide direction for software testing and improve the efficiency of development process. We buil...

Abstract Retraction: [Muhammad Shafiq, Fatemah H. Alghamedy, Nasir Jamal, Tahir Kamal, Yousef Ibrahim Daradkeh, Mohammad Shabaz, Scientific programming using optimized machine learning techniques for software fault prediction to improve quality, IET Software 2023 ( https://doi.org/10.1049/sfw2.12091 )]. The above article from , published online on 6 January in Wiley Online Library (wileyonlinel...