An important open challenge in the area of computational argumentation is the automatic reconstruction of natural language enthymemes. Such argumentative figures are commonly used in natural language human discourse to improve the naturalness and efficiency of speech. They also represent a major challenge when developing computational argumentation systems that need to work with natural language data, since enthymemes bring irregularity to the representations proposed in classical models of argumentation. In this paper, we propose a new framework based on the theory of argumentation schemes aimed at automatically reconstructing natural language enthymemes. The proposed framework consists of a two-module pipeline: (i) scheme classification, and (ii) enthymeme reconstruction. We validate the proposed framework by comparing its performance to a baseline pipeline that does not take the argumentation scheme theory into account. We evaluate the framework by analysing the validity of the complete reconstructed arguments, establishing a new set of baselines that can be used as reference for future work in this direction.

We demonstrate the first prototype of the ADD-up visual analytics system. The Augmented Deliberative Democracy (ADD-up) project aims to enhance public deliberations by providing argument analytics in real time. The system will ultimately take a stenographic feed of a public deliberation meeting, automatically extract the arguments therein and project visual analytics intended to improve the deliberative quality of the event.

This paper introduces a novel method for measuring non-cooperation in dialogue. The key idea is that linguistic non-cooperation can be measured in terms of the extent to which dialogue participants deviate from conventions regarding the proper introduction and discharging of conversational obligations (e.g., the obligation to respond to a question). Previous work on non cooperation has focused mainly on non-linguistic task-related non-cooperation or modelled non-cooperation in terms of special rules describing non-cooperative behaviours. In contrast, we start from rules for normal/correct dialogue behaviour - i.e., a dialogue game - which in principle can be derived from a corpus of cooperative dialogues, and provide a quantitative measure for the degree to which participants comply with these rules. We evaluated the model on a corpus of political interviews, with encouraging results. The model predicts accurately the degree of cooperation for one of the two dialogue game roles (interviewer) and also the relative cooperation for both roles (i.e., which interlocutor in the conversation was most cooperative). Being able to measure cooperation has applications in many areas from the analysis - manual, semi and fully automatic - of natural language interactions to human-like virtual personal assistants, tutoring agents, sophisticated dialogue systems, and role-playing virtual humans.

This paper describes tool support that has been implemented for the Test Template Framework (TTF). The TTF is a model-based testing (MBT) method that is especially well suited for unit testing from Z specifications. Although the TTF is a sound MBT method and it has been widely referenced since its first publication, attention in recent years has decayed. In fact, some have argued that generating abstract test cases following the TTF is a manual task requiring its users to perform complex predicate manipulations. This paper shows that these observations are dubious by describing Fastest, a tool that implements solutions for all these issues and, according to many experiments, produces abstract test cases for more than 80% of the satisfiable test specifications. Furthermore, it is claimed that Fastest fulfils the needs of the Z user community regarding MBT tools, which is supported with a range of case studies. Copyright © 2012 John Wiley & Sons, Ltd.

We have applied Fastest, an implementation of the Test Template Framework, to five real case studies of aerospace software. This involved the formalization in the Z notation of nontrivial parts of each system. One of these models, for instance, formalizes a significant portion of the ECSS-E-70-41A aerospace standard. The models were then fed into Fastest, which automatically generated detailed functional abstract test cases. Since these test cases are independent of any implementation, they can be used to test any of them. Furthermore, we were able to semi-automatically translate them into English so they can be used by domain experts performing independent validation and verification activities.