# Model-based Automated Testing of JavaScript Web Applications via Longer   Test Sequences

**Authors:** Pengfei Gao, Fu Song, Taolue Chen, Yao Zeng, Ting Su

arXiv: 1905.07671 · 2019-05-21

## TL;DR

This paper introduces LJS, a model-based testing tool for JavaScript web apps that uses longer event sequences to improve code coverage efficiently, outperforming existing tools like JSDep.

## Contribution

It presents a novel approach leveraging longer test sequences for higher coverage and implements a tool that demonstrates significant improvements over prior methods.

## Key findings

- LJS achieves 86.4% line coverage in 10 minutes.
- LJS outperforms JSDep by 5.4% on average.
- Longer test sequences lead to higher code coverage.

## Abstract

JavaScript has become one of the most widely used languages for Web development. However, it is challenging to ensure the correctness and reliability of Web applications written in JavaScript, due to their dynamic and event-driven features. A variety of dynamic analysis techniques for JavaScript Web applications have been proposed, but they are limited in either coverage or scalability. In this paper, we propose a model-based automated approach to achieve high code coverage in a reasonable amount of time via testing with longer event sequences. We implement our approach as the tool LJS, and perform extensive experiments on 21 publicly available benchmarks (18,559 lines of code in total). On average, LJS achieves 86.4\% line coverage in 10 minutes, which is 5.4\% higher than that of JSDep, a breadth-first search based automated testing tool enriched with partial order reduction. In particular, on large applications, the coverage of LJS is 11-18\% higher than that of JSDep. Our empirical finding supports that longer test sequences can achieve higher code coverage in JavsScript testing.

## Full text

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## Figures

12 figures with captions in the complete paper: https://tomesphere.com/paper/1905.07671/full.md

## References

55 references — full list in the complete paper: https://tomesphere.com/paper/1905.07671/full.md

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Source: https://tomesphere.com/paper/1905.07671