• Ch. Kishor Kumar
• R Durga

The major objective of software development is to supply quality software efficiently and short period of time. The old development process has different stages every stags have own significance and dependency .As each development stage features a certain outcome or goal. It becomes critical to pick the simplest data processing techniques to realize these goals efficiently. Because the complexity of software applications are growing rapidly day by day, the existing software reliability methods are insufficient to research inter component interactions of modular software systems. The number of test cases could also be extremely large, in order that it's hard to extensively test each software component during a given resource limitations. To get better software, machine learning techniques have been apply to create predictions regarding the failure of software modules by exploit past data and their defects. This paper discusses various reliability estimation techniques and software defect prediction using machine learning techniques.

Software Reliability, Testing, Defect prediction, data mining, Machine learning techniques

" Improve Software Reliability Use Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 9, page no.178-181, September-2021, Available :http://www.jetir.org/papers/JETIRFB06023.pdf

" Improve Software Reliability Use Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 9, page no. pp178-181, September-2021, Available at : http://www.jetir.org/papers/JETIRFB06023.pdf