Rationales and Approaches for Automated Testing of JavaScript and Standard ML

The ever increasing complexity of web applications has brought new demands on automated testing of JavaScript, requiring test-driven development to achieve maintainable code. A contrasting area is testing of Standard ML, another functional language but with important differences. The aim of this thesis is to highlight the main problems with testing behaviour of applications written in these two programming languages, and how these problems relate to development tools and practises. This has been investigated based on the following research questions: What are the testability issues of client-side JavaScript and Standard ML? Which considerations need to be made in order to write stable and maintainable tests? How does testing culture affect productivity and quality of software? Through quantitative interviews, implementation of the DescribeSML testing framework and development with tests in different scenarios, answers to these questions have been sought. The dynamic nature of JavaScript makes it more important to test whereas there are limitations on how Standard ML can be tested imposed by its static type system and immutability. The conclusion was drawn that the main issues for testability are dependency management, how to test graphical interfaces, and maintaining separation of concerns. In order to write stable and maintainable tests, suitable tools and priorities are needed. The impact of testing culture depends on the ability to avoid time-consuming and unreliable tests. Harnessing the technological advancements, making continuous tradeoffs between rigour and simplicity, and applying pragmatism, ingenuity and persistence, are key to overcoming these challenges