Software engineering effort estimation plays a significant role in managing project cost, quality, and time creating software. Researchers have been paying close attention to software during the past few decades, great amount of work has done utilizing variety machine-learning techniques algorithms. In order better effectively evaluate predictions, this study recommends various machine learning...

Although testing effort estimation is a very important task in software project management, it rarely described the literature. There are many difficulties finding any useful methods or tools for this purpose. Solutions to other problems related calculation published much more often. also no research focusing on both and all areas of engineering. To fill gap, we performed systematic literature ...

OVERWHELMING EVIDENCE DOCUMENTS a tendency toward cost and effort overruns in software projects. On average, this overrun seems to be around 30 percent.1 Furthermore, comparing the estimation accuracy of the 1980s with that reported in more recent surveys suggests that the estimation accuracy hasn’t changed much since then. (The only analyses that suggest a strong improvement in estimation accu...

nowadays, software cost estimation (sce) with machine learning techniques are more performance than other traditional techniques which were based on algorithmic techniques. in this paper, we present a new hybrid model of multi-layer perceptron (mlp) artificial neural network (ann) and ant colony optimization (aco) algorithm for high accuracy in sce called multilayer perceptron ant colony optimi...