Event-driven Code Research Articles

Icon2Code: Recommending code implementations for Android GUI components

Event-driven programming plays a crucial role in implementing GUI-based software systems such as Android apps. However, such event-driven code is inherently challenging to design and implement correctly. Despite a significant amount of research to help developers efficiently implement such software, improved approaches are still needed to assist developers in better handling events and associated callback methods.

Handling bidirectional control flow

Pressed by the difficulty of writing asynchronous, event-driven code, mainstream languages have recently been building in support for a variety of advanced control-flow features. Meanwhile, experimental language designs have suggested effect handlers as a unifying solution to programmer-defined control effects, subsuming exceptions, generators, and async–await. However, despite these trends, complex control flow—in particular, control flow that exhibits a bidirectional pattern—remains challenging to manage. We introduce bidirectional algebraic effects, a new programming abstraction that supports bidirectional control transfer in a more natural way. Handlers of bidirectional effects can raise further effects to transfer control back to the site where the initiating effect was raised, and can use themselves to handle their own effects. We present applications of this expressive power, which falls out naturally as we push toward the unification of effectful programming with object-oriented programming. We pin down the mechanism and the unification formally using a core language that makes generalizations to effect operations and effect handlers. The usual propagation semantics of control effects such as exceptions conflicts with modular reasoning in the presence of effect polymorphism—it breaks parametricity. Bidirectionality exacerbates the problem. Hence, we set out to show the core language, which builds on the existing tunneling semantics for algebraic effects, is not only type-safe (no effects go unhandled), but also abstraction-safe (no effects are accidentally handled). We devise a step-indexed logical-relations model, and construct its parametricity and soundness proofs. These core results are fully mechanized in Coq. While a full-featured compiler is left to future work, experiments show that as a first-class language feature, bidirectional handlers can be implemented efficiently.

Dynamics of windscreen wiper blades: Squeal noise, reversal noise and chattering

The motion of a windshield wiper blade is modelled by a mass-spring-damper system on a moving frictional surface. The system dynamics is time-varying, since three different regimes of motion, characterized by different degrees of freedom, are possible. Indeed the system, which schematizes a blade cross-section, can experience stick and slip motions when it is in contact with the glass surface, and free-flight motion when it is detached. The contact between the system and the surface is governed by Stribeck׳s friction law and Poisson׳s impact law, which make the dynamics non-smooth. The model is numerically implemented in an event-driven code, and simulations are performed which reproduce the three basic classes of undesired oscillations observed in the motion of real windscreen wipers, i.e., squeal, reversal and chattering noises. Attention is focused on the causes of these vibrations, and remedies for reducing or avoiding them are proposed.

CrossQuery: A Web Tool for Easy Associative Querying of Transcriptome Data

Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep-sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Microsoft Excel. CrossQuery enables researchers to quickly and freely work with transcriptome and microarray data sets requiring only minimal computer skills. Furthermore, CrossQuery allows growing association of multiple datasets as long as at least one common point of correlated information, such as transcript identification numbers or GO-terms, is shared between samples. For advanced users, the object-oriented plug-in and event-driven code design of both server-side and client-side scripts allow easy addition of new features, data sources and data types.