Experimental study of AHP and CV Requirements Prioritization Techniques | A Experiment to compare two Requirements Prioritization Techniques: AHP and CV - In aspect of Time, Scalability, Accuracy and Ease of use. Este artículo no está disponible.Experimental study of AHP and CV Requirements Prioritization Techniques | A Experiment to compare two Requirements Prioritization Techniques: AHP and CV - In aspect of Time, Scalability, Accuracy and Ease of use

Prioritizing software requirements helps to determine which requirements are most important, and the order in which requirements should be developed and tested throughout the development life cycle. By prioritizing the requirements, software engineers can put focus on a subset of all requirements, and implement these in a particular release. This work aims to analyze two ratio scale prioritization techniques named Analytical Hierarchy Process (AHP) and Cumulative Voting (CV) by a controlled experiment, conducted on software engineering/computer science master students. The experiment was designed to compare time consumption, scalability and accuracy between the two techniques. All these evaluation parameters are combined together to find out which technique is more suitable to use when prioritizing software requirements. The results of the experiment indicate that CV is less time consuming than AHP. It was also found that CV is more scalable than AHP. Furthermore, CV is regarded as more accurate than AHP when measured subjectively in post-test.

Prioritizing software requirements helps to determine which requirements are most important, and the order in which requirements should be developed and tested throughout the development life cycle. By prioritizing the requirements, software engineers can put focus on a subset of all requirements, and implement these in a particular release. This work aims to analyze two ratio scale prioritization techniques named Analytical Hierarchy Process (AHP) and Cumulative Voting (CV) by a controlled experiment, conducted on software engineering/computer science master students. The experiment was designed to compare time consumption, scalability and accuracy between the two techniques. All these evaluation parameters are combined together to find out which technique is more suitable to use when prioritizing software requirements. The results of the experiment indicate that CV is less time consuming than AHP. It was also found that CV is more scalable than AHP. Furthermore, CV is regarded as more accurate than AHP when measured subjectively in post-test.