Research Trends in Software Development Effort Estimation

Developing a software project without the appropriate amount of effort would significantly impede and even fail the project, putting the software developer's quality at risk. Therefore, software development effort estimation (SDEE) is the most critical activity in software engineering. SDEE has seen extensive research, resulting in a massive rise in the literature in a relatively short period. In this regard, it is crucial to identify the significant study topics in software development effort estimation that will assist researchers in understanding and recognizing research trends. This research applied a systematic literature review (SLR) to compile all journals from the predefined search directory about software development effort estimation thoroughly and unbiasedly from 2018 to 2022. This review was a prelude to further research activities in software development effort estimation. Five research topics out of 71 papers have been revealed, including the machine learning approach, algorithmic technique, expert judgement, dataset analysis, and evaluation metric. With 27 journals, deploying a machine learning approach for SDEE is the most discussed research topic. The potential research described in this study can be investigated further in software development effort estimation field.