Currently, programming instructors continually face the problem of helping to debug students' programs. Although there currently exist a number of debuggers and debugging tools in various platforms, most of these projects or products are crafted through the needs of software maintenance, and not through the perspective of teaching of programming. Moreover, most debuggers are too general, meant for experts as well as not user-friendly. We propose a new knowledge-based automated debugger to be used as a user-friendly tool by the students to self-debug their own programs. Stereotyped code (cliche) and bugs cliche will be stored as library of plans in the knowledge-base. Recognition of correct code or bugs is based on pattern matching and constraint satisfaction. Given a syntax error-free program and its specification, this debugger called Adil (Automated Debugger in Learning system) will be able locate, pinpoint and explain logical errors of programs. If there are no errors, it will be able to explain the meaning of the program. Adil is based on the design of the Conceiver, an automated program understanding system developed at Universiti Kebangsaan Malaysia.
Context. Recent studies show that developers spend most of their programming time testing, verifying and debugging software. As applications become more and more complex, developers demand more advanced debugging support to ease the software development process. Inquiry. Since the 70's many debugging solutions were introduced. Amongst them, online debuggers provide a good insight on the conditions that led to a bug, allowing inspection and interaction with the variables of the program. However, most of the online debugging solutions introduce \textit{debugging interference} to the execution of…
Personalized services are in need of a rich and powerful personal knowledge base, i.e. a knowledge base containing information about the user. This paper proposes an approach to extracting personal knowledge from smartphone push notifications, which are used by mobile systems and apps to inform users of a rich range of information. Our solution is based on the insight that most notifications are formatted using templates, while knowledge entities can be usually found within the parameters to the templates. As defining all the notification templates and their semantic rules are impractical due …
Designing blockchain-based applications is a tedious task. Compared to traditional software engineering, software architects cannot rely on previous experiences or proven practices, often formalized as software patterns. Also, the selection of an adequate blockchain technology is difficult without deep knowledge of the technology. This paper introduces Harmonica, a framework for the design and implementation of a blockchain-based application. This framework is divided in three parts: a decision-making engine to recommend a blockchain technology and blockchain-based software patterns relying on…
Data driven research on Android has gained a great momentum these years. The abundance of data facilitates knowledge learning, however, also increases the difficulty of data preprocessing. Therefore, it is non-trivial to prepare a demanding and accurate set of data for research. In this work, we put forward AndroVault, a framework for the Android research composing of data collection, knowledge representation and knowledge extraction. It has started with a long-running web crawler for data collection (both apps and description) since 2013, which guarantees the timeliness of data; With static a…
ARCEAK: An Automated Rule Checking Framework Enhanced with Architectural Knowledge
Shanghai Jiao Tong University（上海交通大学）；Beijing University of Civil Engineering and Architecture（北京建筑大学）；East China Architectural Design & Research Institute（华东建筑设计研究院）
