عنوان مقاله [English]
Accurate estimation of software service development effort is a great challenge both in industry and for academia. The concept of effort is an important and effective parameter in process development and software service management. The reliable estimation of effort helps the project managers to allocate the resources better and manage cost and time so that the project will be finished in the determined time and budget. One of the most popular effort estimation methods is analogy base estimation (ABE) to compare a service with similar historical cases. Unfortunately ABE is not capable of generating accurate results unless determining weights for service features. Therefore, this paper aims to make an efficient and reliable model through combining ABE method and DE algorithm to estimate the software services development effort. In fact, the DE algorithm was utilized for weighting features in the similarity function of the ABE method. The proposed hybrid model has been evaluated on a real data set and two artificial datasets. The obtained results were compared with common effort estimation methods. Obtained values indicate 28, 34 and 19 percentage improvement on the three datasets ISBSG, Moderate, and Severe, respectively.
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