Accurately estimating the code size, cost, effort and schedule is probably the leading vital challenge facing code developers lately. It's major implications for the management of code development as a consequences of every the overestimates and underestimates have direct impact for inflicting damage to code companies. Heap of models square measure projected over the years by varied researchers for ending effort estimations. in addition variety of the studies for early stage effort estimations promoter the importance of early estimations. New paradigms offeralternatives to estimate the code development effort, specially the machine Intelligence (CI) that exploits mechanisms of interaction between humans and processes domain information with the intention of building intelligent systems (IS). Among IS, Artificial Neural Network and logic unit of quantity the two most popular soft computing techniques for code development effort estimation. The aim of this study is to research soft computing techniques inside the there models and to bring thorough review of code and project estimation techniques existing in trade.

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Effort Estimation Fuzzy Logic Soft Computing Cocomo Loc Putnam Model