Context: Most approaches to automated white-box testing consider the client side and the server side of a web application in isolation from each other. Such testers lack a whole-program perspective on the web application under test.
Inquiry: We hypothesise that an additional whole-program perspective would enable the tester to discover which server side errors can be triggered by an actual end user accessing the application through the client, and which ones can only be triggered in hypothetical scenarios.
Approach: In this paper, we explore the idea of employing such a whole-program perspective in inter-process testing. To this end, we develop StackFul, a novel concolic tester which operates on full-stack JavaScript web applications, where both the client and the server side are JavaScript processes communicating via asyn- chronous messages —as enabled by e.g., the WebSocket or Socket.IO-libraries.
Knowledge: We find that the whole-program perspective enables discerning high-priority errors, which are reachable from a particular client, from low-priority errors, which are not accessible through the tested client. Another benefit of the perspective is that it allows the automated tester to construct practical, step-by- step scenarios for triggering server side errors from the end user’s perspective.
Grounding: We apply StackFul on a collection of web applications to evaluate how effective inter- process testing is in distinguishing between high- and low-priority errors. The results show that StackFul correctly classifies the majority of server errors.
Importance: This paper demonstrates the feasibility of inter-process testing as a novel approach for au- tomatically testing web applications. Classifying errors as being of high or low importance aids developers in prioritising bugs that might be encountered by users, and postponing the diagnosis of bugs that are less easily reached.
Original languageEnglish
Number of pages36
JournalThe Art, Science, and Engineering of Programming
Volume5
Issue number2
Publication statusPublished - 1 Oct 2020

    Research areas

  • concolic testing, web applications, automated testing

ID: 53857918