25 research outputs found
Looking Over the Research Literature on Software Engineering from 2016 to 2018
This paper carries out a bibliometric analysis to detect (i) what is the most influential research on software engineering at the moment, (ii) where is being published that relevant research, (iii) what are the most commonly researched topics, (iv) and where is being undertaken that research (i.e., in which countries and institutions). For that, 6,365 software engineering articles, published from 2016 to 2018 on a variety of conferences and journals, are examined.This work has been funded by the Spanish Ministry of Science, Innovation, and Universities under Project
DPI2016-77677-P, the Community of Madrid under Grant RoboCity2030-DIH-CM P2018/NMT-4331, and grant
TIN2016-75850-R from the FEDER funds
An Unsupervised Approach for Discovering Relevant Tutorial Fragments for APIs
Developers increasingly rely on API tutorials to facilitate software
development. However, it remains a challenging task for them to discover
relevant API tutorial fragments explaining unfamiliar APIs. Existing supervised
approaches suffer from the heavy burden of manually preparing corpus-specific
annotated data and features. In this study, we propose a novel unsupervised
approach, namely Fragment Recommender for APIs with PageRank and Topic model
(FRAPT). FRAPT can well address two main challenges lying in the task and
effectively determine relevant tutorial fragments for APIs. In FRAPT, a
Fragment Parser is proposed to identify APIs in tutorial fragments and replace
ambiguous pronouns and variables with related ontologies and API names, so as
to address the pronoun and variable resolution challenge. Then, a Fragment
Filter employs a set of nonexplanatory detection rules to remove
non-explanatory fragments, thus address the non-explanatory fragment
identification challenge. Finally, two correlation scores are achieved and
aggregated to determine relevant fragments for APIs, by applying both topic
model and PageRank algorithm to the retained fragments. Extensive experiments
over two publicly open tutorial corpora show that, FRAPT improves the
state-of-the-art approach by 8.77% and 12.32% respectively in terms of
F-Measure. The effectiveness of key components of FRAPT is also validated.Comment: 11 pages, 8 figures, In Proc. of 39rd IEEE International Conference
on Software Engineering (ICSE'17