Software fault prediction means identification of the faultprone parts in the software. This enables to focus testing activities on those software modules that are predicted as fault-prone. As can be seen in literature, many soft computing techniques are employed to make more accurate predictions previously. However, software fault prediction has not become routine activity in the software deve...

Object-oriented (OO) software have complex dependencies and different change types which frequently affect their maintenance in terms of ripple-effects identification or may likely introduce some faults which are hard to detect. As change is both important and risky, change impact analysis (CIA) is a technique used to preserve the quality of the software system. Several CIA techniques exist but...

Software defect prediction work focuses on the number of defects remaining in a software system. A prediction of the number of remaining defects in an inspected artefact can be used for decision making. An accurate prediction of the number of defects in a software product during system testing contributes not only to the management of the system testing process but also to the estimation of the...

Recently, software defect prediction is an important research topic in the software engineering field. The accurate prediction of defect prone software modules can help the software testing effort, reduce costs, and improve the software testing process by focusing on fault-prone module. Software defect data sets have an imbalanced nature with very few defective modules compared to defect-free o...

Fault prediction is a pre-eminent area of empirical software engineering which has witnessed a huge surge over the last couple of decades. In the development of a fault prediction model, combination of metrics results in better explanatory power of the model. Since the metrics used in combination are often correlated, and do not have an additive effect, the impact of a metric on another i.e. in...

While challenging, the ability to predict faulty modules of a program is valuable to a software project because it can reduce the cost of software development, as well as software maintenance and evolution. Three language-processing based measures are introduced and applied to the problem of fault prediction. The first measure is based on the usage of natural language in a program’s identifiers...

This paper presents an innovative metric based on a class abstraction to capture aspects of software complexity through combinations of class characteristics. The study also used software metrics effectiveness in finding the classes in different error categories for the three versions of Eclipse, the Java-based open-source Integrated Development Environment. Many studies used Logistic regressio...

We present a technique that uses coverage measures in reliability estimation for fault tolerant programs, particularly N-version software. This technique exploits both coverage and time measures collected during testing phases for the individual program versions and the N-version software system for reliability prediction. The application of this technique on the single-version software was pre...

In software engineering there are plenty of applications used for reduced complexity and improved fault prediction approaches. In this paper we study various metrics that are not very much suitable to find fault classes in software. Basically using the concept of metrics to find fault classes and reduced complexity of classes. . various techniques like linear regression, logistic regression, on...