Analogy-based Effort Estimation: A Systematic Mapping of Literature

Abstract

Many research initiatives have been developed in the field of Software Engineering, including the area of software estimation. Software effort estimation techniques based on analogy are applied from historical data of projects, obtained in the early stages of software development. In this context, this paper presents a systematic mapping of the literature, aim to elicit the state of the art on  analogy-based software effort estimation  techniques , indicating challenges and research opportunities. The mapping was done for the period from 2007 to 2017  and was conducted separately for each of the selected sources. The articles found were reviewed according to previously established research and selection criteria, according to the study objectives. Note that the model of estimation by analogy has received more attention and is presented as a promising and feasible technique in relation to the others. The techniques of Adaptive Neuro-fuzzy Inferences (ANFIS), Collaborative Filtering (FC), Radial Basis Functions (FBR) and Deep Learning present a gap to be explored. The results point to a demand for simple and practical estimation techniques, with emphasis on the estimation based on analogies and for the exploration of the artifacts generated in the initial phase of development, mainly in the textual format.