An efficient Software Quality Estimation: Critical Review

In the software Quality to predict the good quality of the programs or the software module is required for software quality estimation. This paper represents that track and detection of potential software faults near the beginning, which is critical in many high assurance systems. On the other hand, creating such accurate quality-estimation design is challenging because the data with noise and unwanted data usually degrades the performance of the whole system or the model. After studying several research woks in this area, we come across with two main problems. First is the noise and second which is the main problem is the parameter on which you can categorize the programs for the betterment. So our survey papers concerted in the two relevant directions and find the pros and cons in the existing traditional techniques. Development practitioners typically construct quality classification or fault prediction models using software metrics and fault data from a previous system release or a similar software project. To establish a proper Software Measurement Methods need a clear understanding of the appropriate data collection, analysis and reporting requirements also. It can be categorized by different accuracy measurement of software model like F-Measure, Odd Ratio and Power. Based on the discussion we also suggest some future enhancements which are useful in software quality estimation