Statechart Slicing

The paper discusses how to reduce a statechart model by slicing. We start with the discussion of control dependencies and data dependencies in statecharts. The and-or dependence graph is introduced to represent control and data dependencies for statecharts. We show how to slice statecharts by using this dependence graph. Our slicing approach helps systems analysts and system designers in understanding system specifications, maintaining software systems, and reusing parts of systems models

Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development

Mobile devices and platforms have become an established target for modern software developers due to performant hardware and a large and growing user base numbering in the billions. Despite their popularity, the software development process for mobile apps comes with a set of unique, domain-specific challenges rooted in program comprehension. Many of these challenges stem from developer difficulties in reasoning about different representations of a program, a phenomenon we define as a "language dichotomy". In this paper, we reflect upon the various language dichotomies that contribute to open problems in program comprehension and development for mobile apps. Furthermore, to help guide the research community towards effective solutions for these problems, we provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference on Program Comprehension (ICPC'18

Crowdsourcing Multiple Choice Science Questions

We present a novel method for obtaining high-quality, domain-targeted multiple choice questions from crowd workers. Generating these questions can be difficult without trading away originality, relevance or diversity in the answer options. Our method addresses these problems by leveraging a large corpus of domain-specific text and a small set of existing questions. It produces model suggestions for document selection and answer distractor choice which aid the human question generation process. With this method we have assembled SciQ, a dataset of 13.7K multiple choice science exam questions (Dataset available at http://allenai.org/data.html). We demonstrate that the method produces in-domain questions by providing an analysis of this new dataset and by showing that humans cannot distinguish the crowdsourced questions from original questions. When using SciQ as additional training data to existing questions, we observe accuracy improvements on real science exams.Comment: accepted for the Workshop on Noisy User-generated Text (W-NUT) 201

Learning Dimensions: Lessons from Field Studies

In this paper, we describe work to investigate the creation of engaging programming learning experiences. Background research informed the design of four fieldwork studies involving a range of age groups to explore how programming tasks could best be framed to motivate learners. Our empirical findings from these four studies, described here, contributed to the design of a set of programming "Learning Dimensions" (LDs). The LDs provide educators with insights to support key design decisions for the creation of engaging programming learning experiences. This paper describes the background to the identification of these LDs and how they could address the design and delivery of highly engaging programming learning tasks. A web application has been authored to support educators in the application of the LDs to their lesson design

A meta-model for dataflow-based rules in smart environments: Evaluating user comprehension and performance

NOTICE: this is the author’s version of a work that was accepted for publication in Science of Computer Programming Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Science of Computer Programming, [Volume 78, Issue 10, 1 October 2013, Pages 1930–1950] DOI 10.1016/j.scico.2012.06.010A considerable part of the behavior in smart environments relies on event-driven and rule specification. Rules are the mechanism most often used to enable user customization of the environment. However, the expressiveness of the rules available to users in editing and other tools is usually either limited or the available rule editing interfaces are not designed for end-users with low skills in programming. This means we have to look for interaction techniques and new ways to define user customization rules. This paper describes a generic and flexible meta-model to support expressive rules enhanced with data flow expressions that will graphically support the definition of rules without writing code. An empirical study was conducted on the ease of understanding of the visual data flow expressions, which are the key elements in our rule proposal. The visual dataflow language was compared to its corresponding textual version in terms of comprehension and ease of learning by teenagers in exercises involving calculations, modifications, writing and detecting equivalences in expressions in both languages. Although the subjects had some previous experience in editing mathematical expressions on spreadsheets, the study found their performance with visual dataflows to be significantly better in calculation and modification exercises. This makes our dataflow approach a promising mechanism for expressing user-customized reactive behavior in Ambient Intelligence (AmI) environments. The performance of the rule matching processor was validated by means of two stress tests to ensure that the meta-model approach adopted would be able to scale up with the number of types and instances in the space. © 2012 Elsevier B.V. All rights reserved.This work received financial support from the Spanish Ministry of Education under the National Strategic Program of Research and Project TSI2010-20488. Our thanks also go to the high school "Collegi Parroquial D. Jose Lluch - Alboraya", especially to the teachers and students that participated in the empirical study reported in this paper. A. Catala is supported by an FPU fellowship from the Ministry of Education of Spain with reference AP2006-00181.Catalá Bolós, A.; Pons, P.; Jaén Martínez, FJ.; Mocholi Agües, JA.; Navarro Martínez, EM. (2013). A meta-model for dataflow-based rules in smart environments: Evaluating user comprehension and performance. Science of Computer Programming. 78(10):1930-1950. doi:10.1016/j.scico.2012.06.010S19301950781