Analysis of data is the foundation of multiple scientific disciplines, manifesting nowadays in complex and diverse scientific workflows often involving exploratory analyses. Such analyses represent a particular case for traditional data engineering workflows, as results may be hard to interpret and judge whether they are correct or not, and where experimentation is a central theme. Input data, or assumptions made about it may be incorrect and may need to be refined – an analogous problem to fault localization in software engineering. Typical techniques assume that a fault is identified, usually by an oracle in the form of a test. The workflows we target however are usually explorative, which makes it hard – if not impossible – to define tests specifying correct behaviour, while spotting irregularities is highly desired. To this end, we advocate data input reduction such that a specified outcome is preserved, aiding debugging. In our proposal, reductions are used as debug hypotheses for data. We outline our bold vision on building engineering support for outcome-preserving input reduction within data analysis workflows, and report on preliminary results.

Anh Duc Vu

Humboldt-Universität zu Berlin

Timo Kehrer

University of Bern

Switzerland

Christos Tsigkanos

University of Bern, Switzerland

NOTE: SUBMITTED A RESEARCH PAPER TO ASE RESEARCH TRACK Application development for the modern Web involves sophisticated engineering workflows which include user interface aspects. Those involve Web elements typically created with HTML/CSS markup and JavaScript-like languages, yielding Web documents. WebMonitor leverages requirements formally specified in a logic able to capture both the layout of visual components as well as how they change over time, as a user interacts with them. Then, requirements are verified upon arbitrary web pages, allowing for automated support for a wide set of use cases in interaction testing and simulation. We position WebMonitor within a developer workflow, where in case of a negative result, a visual counterexample is returned. The monitoring framework we present follows a black-box approach, and as such is independent of the underlying technologies a Web application may be developed with, as well as the browser and operating system used.

Ennio Visconti

TU Wien

Christos Tsigkanos

University of Bern, Switzerland

Laura Nenzi

University of Trieste

Italy