An Empirical Study On Fault Localization And Effective Test Case Selection By Neural Network
Journal Title: Indian Journal of Computer Science and Engineering - Year 2012, Vol 3, Issue 6
Abstract
A Radial basis function (RBF) neural network based fault localization technique is proposed in this paper to assist programmers in locating bugs effectively. Here we employ a three-layered feed forward artificial neural network with a radial basis function for its hidden unit activation and for linear function with its output layer activation. Here the neural network is trained to have a good relationship between the statement coverage information of a test case and its corresponding execution result to get a success or failure. The trained network is then given as an input to a set of virtual test cases, each covering a single statement, and the output of the network, for each virtual test case, is considered to be the suspiciousness of the corresponding covered statement. A statement with a higher suspiciousness has a higher likelihood of contain a bug, and thus, statement can be ranked in descending order of their suspiciousness. The Ranking can then be examined one by one, starting from the top, until a bug is located. Six case studies on different programs were conduced, with each faulty version contain a distinct bug, and the result clearly show that our proposed technique is much more effective than Tarantula, another popular fault localization technique.
Authors and Affiliations
A. Pravin , Dr. S. Srinivasan
Keywords
Related Articles
- EP ID EP98293
- DOI -
- Views 130
- Downloads 0
An Approach with Maintainability, Structured Design and Automation with the Intension of Software Engineering
Scientific software must be personalized for dissimilar execution environments, problem sets, and existing resources to make sure its competence and consistency. Even though adaptation patterns be able to be found in a e...
ADAPTING RULE BASED MACHINE TRANSLATION FROM ENGLISH TO BANGLA
This paper presents the adapting rule based machine translation from English to Bangla. The proposed language translation model relies on rule based methodologies especially fuzzy rules. There are “If - Then” basis rules...
DESIGN OF AN ADAPTIVE CONSTRAINED BASED NEURO-FUZZY CONTROLLER FOR FAULT DETECTION OF A POWER PLANT SYSTEM
This paper proposes an adaptive constraint based framework for fault detection of a complex thermal power plant system. In many complex systems, representation of precise and crisp constraints uses formal specification l...
E-GOVERNMENT DATABASES: A RETROSPECTIVE STUDY
The government is the biggest producer of information and efficient management of the vast amount of data available within the government departments is of utmost importance. Due to the advent of information and communic...
Visual Query in Temporal Database with Multi Dimensions
A wide range of database applications manage time-varying data. In contrast, existing database technology provides little support for managing such data. The research area of temporal databases aims to change this state...