Mining Software Quality from Software Reviews: Research Trends and Open Issues

TL;DR

This paper reviews how sentiment analysis of software reviews can quantify software quality, highlighting research trends and open issues in extracting meaningful insights from user feedback.

Contribution

It investigates the application of opinion mining to extract software quality properties from reviews and discusses major challenges related to software lifecycle and user diversity.

Findings

Sentiment analysis can quantify software quality from reviews.

Major issues include handling diverse users and software lifecycle stages.

Existing methods face customization difficulties.

Abstract

Software review text fragments have considerably valuable information about users experience. It includes a huge set of properties including the software quality. Opinion mining or sentiment analysis is concerned with analyzing textual user judgments. The application of sentiment analysis on software reviews can find a quantitative value that represents software quality. Although many software quality methods are proposed they are considered difficult to customize and many of them are limited. This article investigates the application of opinion mining as an approach to extract software quality properties. We found that the major issues of software reviews mining using sentiment analysis are due to software lifecycle and the diverse users and teams.