API recommendation for event-driven Android application development

Ministry of Education, Singapore under its Academic Research Funding Tier

Accessible user interface support for multi-device ubiquitous applications: architectural modifiability considerations

The market for personal computing devices is rapidly expanding from PC, to mobile, home entertainment systems, and even the automotive industry. When developing software targeting such ubiquitous devices, the balance between development costs and market coverage has turned out to be a challenging issue. With the rise of Web technology and the Internet of things, ubiquitous applications have become a reality. Nonetheless, the diversity of presentation and interaction modalities still drastically limit the number of targetable devices and the accessibility toward end users. This paper presents webinos, a multi-device application middleware platform founded on the Future Internet infrastructure. Hereto, the platform's architectural modifiability considerations are described and evaluated as a generic enabler for supporting applications, which are executed in ubiquitous computing environments

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

AI Dining Suggestion App

Trying to decide what to eat can sometimes be challenging and time-consuming for people. Google and Yelp have large scale data sets of restaurant information as well as Application Program Interfaces (APIs) for using them. This restaurant data includes time, price range, traffic, temperature, etc. The goal of this project is to build an app that eases the process of finding a restaurant to eat. This app has a Tinder-like user friendly User Interface (UI) design to change the common way that lists of restaurants are presented to users on mobile apps. It also uses the help of Artificial Intelligence (AI) with neural networks to train both supervised and unsupervised learning models that can learn from one\u27s dining pattern over time to make better suggestions at any time

An Intuitive Control API for Catroid

In this research, the main objective is to develop an intuitive control API in Catroid to enhance its usability as a graphical programming tool for children and study the human-mobile interaction and experience made possible with this control API. Another objective is to develop this control API in open source development method and benchmark it with the typical software development method. It would greatly enrich user experience if Catroid can provide support for implementing intuitive control concepts to enhance its usability for children. But currently Catroid do not have control API support to develop intuitive user interaction with the application. In brief, an intuitive control API is missing in Catroid. Without such an API, the potential of Catroid as a programming tool cannot be unleashed. This research studies the maximization programming power of Catroid and advancement of control API in Catroid into a more intuitive form. This research studies the Open Source Development Model used to develop the control API. The scope of prototype will only covers locating direction, tilting, turning, and shaking motions as the new intuitive control made possible in Catroid The research methodology is Open Source Development Methodology (OSDM) and the Test-Driven Development Method with Extreme Programming is used for code development. The objective of OSDM is to utilize the online community who is the user and developers of Catroid to review and test source code to improve the software quality. The intuitive control API where phone sensors are integrated will further improve the user interaction and experience both in using Catroid and its application. The intuitive control API consists of sensor variables and If-Then-Else Command Block. The If-Then-Else Command Block acts as the control and the sensor variables make the control become intuitive. Accelerometer and orientation sensor are implemented in this control API where each of the sensors contributed 3 different values acted as the sensor variables: X-Sensor Acceleration, Y-Sensor Acceleration, Z-Sensor Acceleration, Azimuth, Pitch, and Roll. These sensor variables can be assigned to or removed from any text field in the Command Blocks using the Formula Editor. The usage of the intuitive control API is simple and straight forward. When a sensor variable is assigned to one of the fields in If-Then-Else Command Blocks, the intuitive control is developed. The Command Blocks in between the If-Statement Command Block and End of If Command Block will be executed whenever the logic condition in the If-Statement is true. Various intuitive user interactions could be developed depending on the creativity of users. The most popular intuitive user interactions are through locating direction, tilting, turning and shaking motions. Open Source Development Method allows developers to redefine the user requirements along with the software development which reduce the risk of software failure in the end of development

A Behavior-Driven Recommendation System for Stack Overflow Posts

Developers are often tasked with maintaining complex systems. Regardless of prior experience, there will inevitably be times in which they must interact with parts of the system with which they are unfamiliar. In such cases, recommendation systems may serve as a valuable tool to assist the developer in implementing a solution. Many recommendation systems in software engineering utilize the Stack Overflow knowledge-base as the basis of forming their recommendations. Traditionally, these systems have relied on the developer to explicitly invoke them, typically in the form of specifying a query. However, there may be cases in which the developer is in need of a recommendation but unaware that their need exists. A new class of recommendation systems deemed Behavior-Driven Recommendation Systems for Software Engineering seeks to address this issue by relying on developer behavior to determine when a recommendation is needed, and once such a determination is made, formulate a search query based on the software engineering task context. This thesis presents one such system, StackInTheFlow, a plug-in integrating into the IntelliJ family of Java IDEs. StackInTheFlow allows the user to intervi act with it as a traditional recommendation system, manually specifying queries and browsing returned Stack Overflow posts. However, it also provides facilities for detecting when the developer is in need of a recommendation, defined when the developer has encountered an error messages or a difficulty detection model based on indicators of developer progress is fired. Once such a determination has been made, a query formulation model constructed based on a periodic data dump of Stack Overflow posts will automatically form a query from the software engineering task context extracted from source code currently open within the IDE. StackInTheFlow also provides mechanisms to personalize, over time, the results displayed to a specific set of Stack Overflow tags based on the results previously selected by the user. The effectiveness of these mechanisms are examined and results based the collection of anonymous user logs and a small scale study are presented. Based on the results of these evaluations, it was found that some of the queries issued by the tool are effective, however there are limitations regarding the extraction of the appropriate context of the software engineering task yet to overcome

International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome