University of Sannio

About: University of Sannio is a education organization based out in Benevento, Italy. It is known for research contribution in the topics: Gravitational wave & LIGO. The organization has 1278 authors who have published 6125 publications receiving 167577 citations. The organization is also known as: Università degli Studi del Sannio & Universita degli Studi del Sannio.

Sentiment analysis for software engineering: how far can we go?

Abstract: Sentiment analysis has been applied to various software engineering (SE) tasks, such as evaluating app reviews or analyzing developers' emotions in commit messages. Studies indicate that sentiment analysis tools provide unreliable results when used out-of-the-box, since they are not designed to process SE datasets. The silver bullet for a successful application of sentiment analysis tools to SE datasets might be their customization to the specific usage context. We describe our experience in building a software library recommender exploiting developers' opinions mined from Stack Overflow. To reach our goal, we retrained---on a set of 40k manually labeled sentences/words extracted from Stack Overflow---a state-of-the-art sentiment analysis tool exploiting deep learning. Despite such an effort- and time-consuming training process, the results were negative. We changed our focus and performed a thorough investigation of the accuracy of commonly used tools to identify the sentiment of SE related texts. Meanwhile, we also studied the impact of different datasets on tool performance. Our results should warn the research community about the strong limitations of current sentiment analysis tools.

Search for gravitational waves from binary inspirals in S3 and S4 LIGO data

Abstract: We report on a search for gravitational waves from the coalescence of compact binaries during the third and fourth LIGO science runs. The search focused on gravitational waves generated during the inspiral phase of the binary evolution. In our analysis, we considered three categories of compact binary systems, ordered by mass: (i) primordial black hole binaries with masses in the range 0.35M_⊙

The Impact of API Change- and Fault-Proneness on the User Ratings of Android Apps

Abstract: The mobile apps market is one of the fastest growing areas in the information technology. In digging their market share, developers must pay attention to building robust and reliable apps. In fact, users easily get frustrated by repeated failures, crashes, and other bugs; hence, they abandon some apps in favor of their competition. In this paper we investigate how the fault- and change-proneness of APIs used by Android apps relates to their success estimated as the average rating provided by the users to those apps. First, in a study conducted on 5,848 (free) apps, we analyzed how the ratings that an app had received correlated with the fault- and change-proneness of the APIs such app relied upon. After that, we surveyed 45 professional Android developers to assess (i) to what extent developers experienced problems when using APIs, and (ii) how much they felt these problems could be the cause for unfavorable user ratings. The results of our studies indicate that apps having high user ratings use APIs that are less fault- and change-prone than the APIs used by low rated apps. Also, most of the interviewed Android developers observed, in their development experience, a direct relationship between problems experienced with the adopted APIs and the users’ ratings that their apps received.