Analyzing the understandability of Requirements Engineering languages for CSCW systems: A family of experiments

Abstract

Context: A collaborative system is a special kind of software whose users can perform collaboration, communication and collaboration tasks. These systems usually have a high number of non-functional requirements, resulting from the users¿ need of being aware of other users with whom to collaborate, that is, the workspace awareness. Objective: This paper aims at evaluating two Requirements Engineering languages i and CSRML (an extension of i ) in order to determine which is the most suitable one to specify requirements of collaborative systems, taking into account their special characteristics regarding collaboration and awareness. Method: We performed a family of experiments comprising an original experiment and two replicas. They were performed by 30, 45 and 9 Computer Science students, respectively, from Spain and Argentina. These subjects filled in two understandability questionnaires once they analyzed the requirements models of two systems: an e-learning collaborative system and a conference review system with some collaborative aspects support. Both models were specified by using the evaluated languages. Results: The statistical analysis of the family of experiments showed that the understandability was higher for the models specified with CSRML than for those specified with i , especially for collaborative aspects. This result was also confirmed by the meta-analysis conducted. Conclusions: CSRML surpasses i when modeling collaborative systems requirements models due to the specific expressiveness introduced to represent collaboration between users and awareness and the new resorts to manage actors and roles.