A reification calculus for model-oriented software specification

This paper presents a transformational approach to the derivation of implementations from model-oriented specifications of abstract data types. The purpose of this research is to reduce the number of formal proofs required in model refinement, which hinder software development. It is shown to be appli- cable to the transformation of models written in Meta-iv (the specification lan- guage of Vdm) towards their refinement into, for example, Pascal or relational DBMSs. The approach includes the automatic synthesis of retrieve functions between models, and data-type invariants. The underlying algebraic semantics is the so-called final semantics “`a la Wand”: a specification “is” a model (heterogeneous algebra) which is the final ob ject (up to isomorphism) in the category of all its implementations. The transformational calculus approached in this paper follows from exploring the properties of finite, recursively defined sets. This work extends the well-known strategy of program transformation to model transformation, adding to previous work on a transformational style for operation- decomposition in META-IV. The model-calculus is also useful for improving model-oriented specifications.(undefined

Return of the Great Spaghetti Monster : Learnings from a Twelve-Year Adventure in Web Software Development

The widespread adoption of the World Wide Web has fundamentally changed the landscape of software development. Only ten years ago, very few developers would write software for the Web, let alone consider using JavaScript or other web technologies for writing any serious software applications. In this paper, we reflect upon a twelve-year adventure in web development that began with the development of the Lively Kernel system at Sun Microsystems Labs in 2006. Back then, we also published some papers that identified important challenges in web-based software development based on established software engineering principles. We will revisit our earlier findings and compare the state of the art in web development today to our earlier learnings, followed by some reflections and suggestions for the road forward.Peer reviewe

Unification modulo Lists with Reverse, Relation with Certain Word Equations

International audienceDecision procedures for various list theories have been investigated in the literature with applications to automated verification. Here we show that the unifiability problem for some list theories with a \emph{reverse} operator is NP-complete. We also give a unifiability algorithm for the case where the theories are extended with a \emph{length} operator on lists

Patient-Adaptive Ectopic Beat Classification using Active Learning

A major challenge in applying machine learning techniques to the problem of heartbeat classification is dealing effectively with inter-patient differences in electrocardiograms (ECGs). Inter-patient differences create a need for patient-specific classifiers, since there is no a priori reason to assume that a classifier trained on data from one patient will yield useful results when applied to a different patient. Unfortunately, patient-specific classifiers come at a high cost, since they require a labeled training set. Using active learning, we show that one can drastically reduce the amount of patient-specific labeled training data required to build a highly accurate patient-specific binary heartbeat classifier for identifying ventricular ectopic beats. Tested on all 48 half-hour ECG recordings from the MIT-BIH Arrhythmia Database, our approach achieves an average sensitivity of 96.2% and specificity of 99.9%. The average number of beats needed to train each patient-specific classifier was less than 37 beats, approximately 30 seconds of data