Itzel Morales-Ramirez

Providing Foundation for User Feedback Concepts by Extending a Communication Ontology

The term user feedback is becoming widely used in requirements engineering (RE) research to refer to the comments and evaluations that users express upon having experienced the use of a software application or service. This explicit feedback takes place in virtual spaces (e.g., issue tracking systems, app stores), aiming, for instance, at reporting on discovered bugs or requesting new features. Founding the notion of explicit user feedback with the use of an ontology may support a deep understanding of the feedback nature, as well as contribute to the development of tool-components for its analysis at use of requirements analysts. In this paper, we present a user feedback ontology as an extension of an existing communication ontology. We describe how we built it, along with a set of competency questions, and illustrate its applicability on an example taken from a collaborative communication related to RE for software evolution.

Towards Supporting the Analysis of Online Discussions in OSS Communities: A Speech-Act Based Approach

Open-Source Software (OSS) community members report bugs, request features or clarifications by writing messages (in unstructured natural language) to mailing lists. Analysts examine them dealing with an effort demanding and error prone task, which requires reading huge threads of emails. Automated support for retrieving relevant information and particularly for recognizing discussants’ intentions (e.g., suggesting, complaining) can support analysts, and allow them to increase the performance of this task. Online discussions are almost synchronous written conversations that can be analyzed applying computational linguistic techniques that build on the speech act theory. Our approach builds on this observation. We propose to analyze OSS mailing-list discussions in terms of the linguistic and non-linguistic acts expressed by the participants, and provide a tool-supported speech-act analysis method. In this paper we describe this method and discuss how to empirically evaluate it. We discuss the results of the first execution of an empirical study that involved 20 subjects.

Analysis of Online Discussions in Support of Requirements Discovery

Feedback about software applications and services that end-users express through web-based communication platforms represents an invaluable knowledge source for diverse software engineering tasks, including requirements elicitation. Research work on automated analysis of textual messages in app store reviews, open source software (OSS) mailing-lists and user forums has been rapidly increasing in the last five years. NLP techniques are applied to filter out irrelevant data, text mining and automated classification techniques are then used to classify messages into different categories, such as bug report and feature request. Our research focuses on online discussions that take place in user forums and OSS mailing-lists, and aims at providing automated analysis techniques to discover contained requirements. In this paper, we present a speech-acts based analysis technique, and experimentally evaluate it on a dataset taken from a widely used OSS project.