Automated COSMIC Function Point measurement using a requirements engineering ontology

• A requirements engineering ontology was designed in a telecommunications company setting.
• COSMIC Function Point concepts were also designed as a part of proposed ontology.
• A mapping was proposed between the concepts of requirements ontology and COSMIC Function Point.
• An automatic functional size measurement method and tool was designed and implemented.
• Experimental results show that method works correctly and eliminates effort and subjectivity coming from manual measurement.

ContextThere are two interrelated difficulties in requirements engineering processes. First, free-format modelling practices in requirements engineering activities may lead to low quality artefacts and productivity problems. Second, the COSMIC Function Point Method is not yet widespread in the software industry because applying measurement rules to imprecise and ambiguous textual requirements is difficult and requires additional human measurement effort. This challenge is common to all functional size measurement methods.ObjectiveIn this study, alternative solutions have been investigated to address these two difficulties. Information created during the requirements engineering process is formalized as an ontology that also becomes a convenient model for transforming requirements into COSMIC Function Point Method concepts.MethodA method is proposed to automatically measure the functional size of software by using the designed ontology. The proposed method has been implemented as a software application and verified with real projects conducted within the ICT department of a leading telecommunications provider in Turkey.ResultsWe demonstrated a novel method to measure the functional size of software in COSMIC FP automatically. It is based on a newly developed requirements engineering ontology. Our proposed method has several advantages over other methods explored in previous research.ConclusionManual and automated measurement results are in agreement, and the tool is promising for the company under study and for the industry at large.