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

How FAIR can you get? Image Retrieval as a Use Case to calculate FAIR Metrics

A large number of services for research data management strive to adhere to the FAIR guiding principles for scientific data management and stewardship. To evaluate these services and to indicate possible improvements, use-case-centric metrics are needed as an addendum to existing metric frameworks. The retrieval of spatially and temporally annotated images can exemplify such a use case. The prototypical implementation indicates that currently no research data repository achieves the full score. Suggestions on how to increase the score include automatic annotation based on the metadata inside the image file and support for content negotiation to retrieve the images. These and other insights can lead to an improvement of data integration workflows, resulting in a better and more FAIR approach to manage research data.Comment: This is a preprint for a paper accepted for the 2018 IEEE conferenc

Approaches to Semantic Web Services: An Overview and Comparison

Abstract. The next Web generation promises to deliver Semantic Web Services (SWS); services that are self-described and amenable to automated discovery, composition and invocation. A prerequisite to this, however, is the emergence and evolution of the Semantic Web, which provides the infrastructure for the semantic interoperability of Web Services. Web Services will be augmented with rich formal descriptions of their capabilities, such that they can be utilized by applications or other services without human assistance or highly constrained agreements on interfaces or protocols. Thus, Semantic Web Services have the potential to change the way knowledge and business services are consumed and provided on the Web. In this paper, we survey the state of the art of current enabling technologies for Semantic Web Services. In addition, we characterize the infrastructure of Semantic Web Services along three orthogonal dimensions: activities, architecture and service ontology. Further, we examine and contrast three current approaches to SWS according to the proposed dimensions

The INCF Digital Atlasing Program: Report on Digital Atlasing Standards in the Rodent Brain

The goal of the INCF Digital Atlasing Program is to provide the vision and direction necessary to make the rapidly growing collection of multidimensional data of the rodent brain (images, gene expression, etc.) widely accessible and usable to the international research community. This Digital Brain Atlasing Standards Task Force was formed in May 2008 to investigate the state of rodent brain digital atlasing, and formulate standards, guidelines, and policy recommendations.

Our first objective has been the preparation of a detailed document that includes the vision and specific description of an infrastructure, systems and methods capable of serving the scientific goals of the community, as well as practical issues for achieving
the goals. This report builds on the 1st INCF Workshop on Mouse and Rat Brain Digital Atlasing Systems (Boline et al., 2007, _Nature Preceedings_, doi:10.1038/npre.2007.1046.1) and includes a more detailed analysis of both the current state and desired state of digital atlasing along with specific recommendations for achieving these goals

Enriching Existing Test Collections with OXPath

Extending TREC-style test collections by incorporating external resources is a time consuming and challenging task. Making use of freely available web data requires technical skills to work with APIs or to create a web scraping program specifically tailored to the task at hand. We present a light-weight alternative that employs the web data extraction language OXPath to harvest data to be added to an existing test collection from web resources. We demonstrate this by creating an extended version of GIRT4 called GIRT4-XT with additional metadata fields harvested via OXPath from the social sciences portal Sowiport. This allows the re-use of this collection for other evaluation purposes like bibliometrics-enhanced retrieval. The demonstrated method can be applied to a variety of similar scenarios and is not limited to extending existing collections but can also be used to create completely new ones with little effort.Comment: Experimental IR Meets Multilinguality, Multimodality, and Interaction - 8th International Conference of the CLEF Association, CLEF 2017, Dublin, Ireland, September 11-14, 201

Context-Sensitive Code Completion

Developers depend extensively on software frameworks and libraries to deliver the products on time. While these frameworks and libraries support software reuse, save development time, and reduce the possibility of introducing errors, they do not come without a cost. Developers need to learn and remember Application Programming Interfaces (APIs) for effectively using those frameworks and libraries. However, APIs are difficult to learn and use. This is mostly due to APIs being large in number, they may not be properly documented, and finally there exist complex relationships between various classes and methods that make APIs difficult to learn. To support developers using those APIs, this thesis focuses on the code completion feature of modern integrated development environments (IDEs). As a developer types code, a code completion system offers a list of completion proposals through a popup menu to navigate and select. This research aims to improve the current state of code completion systems in discovering APIs. Towards this direction, a case study on tracking source code lines has been conducted to better understand capturing code context and to evaluate the benefits of using the simhash technique. Observations from the study have helped to develop a simple, context-sensitive method call completion technique, called CSCC. The technique is compared with a large number of existing code completion techniques. The notion of context proposed in CSCC can even outweigh graph-based statistical language models. Existing method call completion techniques leave the task of completing method parameters to developers. To address this issue, this thesis has investigated how developers complete method parameters. Based on the analysis, a method parameter completion technique, called PARC, has been developed. To date, the technique supports the largest number of expressions to complete method parameters. The technique has been implemented as an Eclipse plug-in that demonstrates the proof of the concept. To meet application-specific requirements, software frameworks need to be customized via extension points. It was observed that developers often pass a framework related object as an argument to an API call to customize default aspects of application frameworks. To enable such customizations, the object can be created by extending a framework class, implementing an interface, or changing the properties of the object via API calls. However, it is both a common and non-trivial task to find all the details related to the customizations. To address this issue, a technique has been developed, called FEMIR. The technique utilizes partial program analysis and graph mining technique to detect, group, and rank framework extension examples. The tool extends existing code completion infrastructure to inform developers about customization choices, enabling them to browse through extension points of a framework, and frequent usages of each point in terms of code examples. Findings from this research and proposed techniques have the potential to help developers to learn different aspects of APIs, thus ease software development, and improve the productivity of developers

Enhancing Mobile App User Understanding and Marketing with Heterogeneous Crowdsourced Data: A Review

© 2013 IEEE. The mobile app market has been surging in recent years. It has some key differentiating characteristics which make it different from traditional markets. To enhance mobile app development and marketing, it is important to study the key research challenges such as app user profiling, usage pattern understanding, popularity prediction, requirement and feedback mining, and so on. This paper reviews CrowdApp, a research field that leverages heterogeneous crowdsourced data for mobile app user understanding and marketing. We first characterize the opportunities of the CrowdApp, and then present the key research challenges and state-of-the-art techniques to deal with these challenges. We further discuss the open issues and future trends of the CrowdApp. Finally, an evolvable app ecosystem architecture based on heterogeneous crowdsourced data is presented