Abstract: In today's digital world, life without computers is not possible. Nearly everything around us is on an intelligent system, helping us to lead life in a better way. The revolution brought by smart systems has increased the global productivity and has benefited the world. Intelligent Systems are useless without software. For excellence in intelligent systems, there is strong need to develop more and more reliable software. Thus, the role played by the intelligent system is appreciated in industry, education, faults prediction, information, banking and social media etc. Access to online payment, entertainment, banking systems, chatting, bill payments, organization management, nuclear reactors etc. has become easier, smarter and faster in day to day life. The goal of this research is to develop Intelligent Software System for identifying defects based in existing software modules using Machine Learning techniques. The just-in-time (JIT) defect removal ensures software quality so higher priority defects can be removed thereby enhancing reliability of the software system. Intelligent Software System (ISS) comprises programs, methodologies, rules and related documentation and information that empower the client to collaborate with a computer, its equipment i.e. hardware, or perform errands. According to Pressman, it performs a dual role. Sometimes, it behaves as a product and sometimes it becomes a vehicle for delivering a product. When software is a product, it executes two functions; firstly it transforms information i.e. produces, manages, acquires, modifies, displays, or transmits information and secondly it delivers computing potential of hardware and networks. Software controls other programs, communication of information, and helps in building other software products. But like any other invention, software has drawbacks. When the computer system or programming software demonstrates failure, a disappointment or breakdown occurs and the influence of disappointments leads to financial harm prompting monstrous loss of human lives and cash.

Key words: big data, PMAY, real estate price prediction, intelligent real estate system, soft computing, SVM, LSTSVM