Efficient JavaScript Mutation Testing

TL;DR: This thesis enhances the understanding of testing technique evaluations by providing an overview of the state of the art in research by utilizing a systematic mapping study; structuring the field and identifying research gaps and publication trends.

TL;DR: This thesis introduces new techniques for identifying, evolving and selecting input subdomains that can be sampled at random to produce efficient test suites which achieve a high level of mutation adequacy, and so are expected to be efficient at finding faults.

TL;DR: Investigating whether GPU programming can benefit from mutation testing and proposing nine GPU-specific mutation operators based on the core syntax differences between CPU and GPU programming, which show that mutation testing can effectively evaluate the test quality of GPU programs.

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.

TL;DR: Google as discussed by the authors is a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems.

TL;DR: Several properties of the graph-theoretic complexity are proved which show, for example, that complexity is independent of physical size and complexity depends only on the decision structure of a program.

TL;DR: In this paper, a graph-theoretic complexity measure for managing and controlling program complexity is presented. But the complexity is independent of physical size, and complexity depends only on the decision structure of a program.

TL;DR: Several of Chidamber and Kemerer's OO metrics appear to be useful to predict class fault-proneness during the early phases of the life-cycle and are better predictors than "traditional" code metrics, which can only be collected at a later phase of the software development processes.