A suite of visual languages for model-driven development of statistical surveys and services

Objective: To provide statistician end users with a visual language environment for complex statistical survey design and implementation. Methods: We have developed, in conjunction with professional statisticians, the Statistical Design Language (SDL), an integrated suite of visual languages aimed at supporting the process of designing statistical surveys, and its support environment, SDLTool. SDL comprises five diagrammatic notations: survey diagrams, data diagrams, technique diagrams, task diagrams and process diagrams. SDLTool provides an integrated environment supporting design, coordination, execution, sharing and publication of complex statistical survey techniques as web services. SDLTool allows association of model components with survey artefacts, including data sets, metadata, and statistical package analysis scripts, with the ability to execute elements of the survey design model to implement survey analysis. Results: We describe three evaluations of SDL and SDLTool: use of the notation by expert statistician to design and execute surveys; useability evaluation of the environment; and assessment of several generated statistical analysis web services. Conclusion: We have shown the effectiveness of SDLTool for supporting statistical survey design and implementation. Practice implications: We have developed a more effective approach to supporting statisticians in their survey design work.

A preliminary survey of factors affecting software testers

Most software testing research has focused on the development of systematic, standardised, and automated testing methodologies and tools. The abilities and expertise needed to apply such techniques and tools - such as personality traits, education, and experience - have attracted a comparatively small amount of research attention. However, the limited research in the area to date provides some indication that the human traits of software testers are important for effective testing. This paper presents the opinions of software testers themselves, collected through an online survey, on the importance of a variety of factors that influence effective testing, including testing-specific training, experience, skills, and human qualities like dedication and general intelligence. The survey responses strongly suggest that while testing tools and training are important, human factors were similarly considered highly important. Domain knowledge, experience, intelligence, and dedication, amongst other traits, were considered crucial for a software tester to be effective. As such, while systematic methodologies are important, the individual most clearly does matter in software testing. The results of our research have implications for education, recruitment, training and management of software testers.