A Systematic Mapping Study driven by the margin of error

Until recently, many Systematic Literature Reviews (SLRs) and Systematic Mapping Studies (SMSs) have been proposed. However, when SMS is performed on a broad topic with a large amount of primary studies, the cost of assessment of all primary studies requires unjustified resources. In this paper, a new approach is introduced for performing SMSs, called SMS driven by the margin of error. The main objective of the described work was to decrease the assessment cost of primary studies by stopping the process of classification of primary studies when enough evidence has been collected. We introduced a statistical approach with random sampling and a margin of error into the design of SMSs when a topic under discussion is broad with a large number of primary studies. In this paper, SMS driven by the margin of error was applied on three different use cases: SMS on Domain-Specific Languages, SMS on Template-based Code Generation, and SMS on Software Reliability Modeling, where it was shown that the proposed approach reduced the cost of assessing primary studies and quantified the reliability of SMS.