Research Paper | Artificial Neural Network

RESEARCH PAPER 0
Article Name: H.K., Dam, T. Tran and, A., Ghose, “Explainable software analytics,” In
Proceedings of the 40th International Conference on Software Engineering: New Ideas
and Emerging Results, vol. 12, no. 6, pp. 53-56, 2018.
Artificial Neural Network

RESEARCH PAPER 1
Table of Contents
Introduction.................................................................................................................... 2
The intention of the paper.................................................................................................. 2
Research methods............................................................................................................ 3
Research approach........................................................................................................ 3
Research design........................................................................................................... 3
Data collection methods................................................................................................. 4
Data analysis............................................................................................................... 4
Problems highlighted by the writers...................................................................................... 4
Results and findings......................................................................................................... 5
Conclusions of the paper.................................................................................................... 5
Conclusion..................................................................................................................... 5
References..................................................................................................................... 7

RESEARCH PAPER 2
Introduction
Artificial neural networks are defined as the computing networks which are inspired by the
biological neural networks that establish animal intelligence. It is based on the combination of
linked nodes which are defined as artificial neurons that convert models in biological
intelligence. Software analytics is a part of artificial intelligence that helps companies to analyze
larger data sets and enhance the quality of software and services effectively. The aim of the
investigation is to evaluate the concept behind software analytics and review a journal article
based on artificial neural networks. The chosen paper is “Explainable Software Analytics” which
was presented by Hoa, Truyen and Aditya in the year 2018 [1]. This research will include
various sections such as the intention of paper, utilized research methodologies, issues described
in the paper, results, and conclusion.
The intention of the paper
According to the writers, software analytics is a major topic for the investigation and many
companies adopted such technology in the business activities recently that helped to manage
larger datasets effectively. It is determined that most of the software analytics techniques are
based on machine learning programs that help to develop prediction networks for numerous
software engineering tasks including defect prediction, API recommendations, threat
identification and many more. In this paper, the investigators determined the major
characteristics of software analytics and evaluated explainable software analytics models [2].
Using software analytic networks, the companies can enhance the performance of computing
software and the accuracy of predictive models can be enhanced using deep neural networks and
ensemble techniques. It is highlighted that the lack of explainability outcomes in the lack of trust
may lead the business reluctance for adopting software analytics in the workplace. The
researchers argued that the larger predictive performance at the time of testing can develop some
trust in the models which can help to manage larger datasets and perform complex tasks easily.
The major research question of the paper is “how might companies evaluate explainability of
software analytics frameworks and how do they develop explanations from software analytics?”
For addressing such a question, the writers included viewpoints of other investigators and