A Proposal of Code Completion Problem for Java Programming Learning Assistant System

To enhance Java programming educations in schools, we have developed a Web-based Java Programming Learning Assistant System (JPLAS) that provides a variety of programming assignments to cover different learning stages. For the first stage, JPLAS offers the element fill-in-blank problem where students study the grammar and code reading through filling the blank elements, composed of reserved words, identifiers, and control symbols, in a high-quality code. Unfortunately, it has been observed that students can fill the blanks without reading the code carefully, because the choice is limited for each blank. In this paper, we propose a code completion problem as a generalization of the element fill-in-blank problem. To solve the drawback, it does not explicitly show blank locations in the code, which expects students to carefully read the code to understand the grammar and code structure. The correctness of the answer is verified through string matching of each statement with the filled elements and the corresponding correct one. Besides, to encourage students to study readable code writing, the correct statement satisfies the coding rules including the spaces. For evaluations, we generated six code completion and element fill-in-blank problems respectively, and asked ten students in two universities to solve them. Their solution results show that the code completion problem is much harder than the element fill-in-blank problem, and requires far deeper code reading and understanding of coding rules

A software architecture for Java programming learning assistant system

For advancements of Java programming educations, we have developed a Web-based Java Programming Learning System (JPLAS). JPLAS provides four problems with different levels, namely, element fill-inblank problem, value trace problem, statement fill-in-blank problem, and code writing problem, to cover students at different learning stages. Unfortunately, since JPLAS has been implemented by a number of students who studied in our group at different years, the code has become complex and redundant, which makes further extensions of JPLAS extremely hard. In this paper, we propose a software architecture for JPLAS to avoid redundancy. Based on the MVC model, our proposal uses Java for the model (M), HTML/CSS/JavaScript for the view (V), and JSP for the controller (C). Besides, adopting a design pattern, the marking functions of the four problems are implemented uniformly. For evaluations, after JPLAS is implemented with this architecture, the number of code files is compared with that of the previous implementation, and the number of additional files is examined for two new functions

nExaminer: A Semi-automated Assignment Assessment Framework for Moodle.

In this paper, we present the nExaminer framework for semi-automated assignment assessment in an open source virtual learning system, namely, Moodle. The motivation for developing the framework is established on the observation of a major problem associated with traditional assignment assessment in Moodle - managing an effective relationship between the instructor and the students is difficult. Thus, the design and implementation of the nExaminer framework is discussed, along with the advantages it provides to both students and instructors. Experimental results with the nExaminer framework have been encouraging. It shows that the framework provides instructors with the ability to semi-automatically generate subjective feedback and automate the process of objective assessment within Moodle in an efficient manner. Moreover, the results also manifest that students are motivated by the usage of automated objective assessment in the nExaminer framework

Gradually learning programming supported by a growable programming language

Learning programming is a difficult task. The learning process is particularly disorienting when you are approaching programming for the first time. As a student you are exposed to several new concepts (control flow, variable, etc. but also coding, compiling etc.) and new ways to think (algorithms). Teachers try to expose the students gradually to the new concepts by presenting them one by one but the tools at student's disposal do not help: they provide support, suggestion and documentation for the full programming language of choice hampering the teacher's efforts. On the other side, students need to learn real languages and not didactic languages. In this work we propose an approach to gradually teaching programming supported by a programming language that grows---together with its implementation---along with the number of concepts presented to the students. The proposed approach can be applied to the teaching of any programming language and some experiments with Javascript are reported

A Systematic Mapping Study of Code Quality in Education -- with Complete Bibliography

While functionality and correctness of code has traditionally been the main focus of computing educators, quality aspects of code are getting increasingly more attention. High-quality code contributes to the maintainability of software systems, and should therefore be a central aspect of computing education. We have conducted a systematic mapping study to give a broad overview of the research conducted in the field of code quality in an educational context. The study investigates paper characteristics, topics, research methods, and the targeted programming languages. We found 195 publications (1976-2022) on the topic in multiple databases, which we systematically coded to answer the research questions. This paper reports on the results and identifies developments, trends, and new opportunities for research in the field of code quality in computing education

An automated closed-loop framework to enforce security policies from anomaly detection

Due to the growing complexity and scale of IT systems, there is an increasing need to automate and streamline routine maintenance and security management procedures, to reduce costs and improve productivity. In the case of security incidents, the implementation and application of response actions require significant efforts from operators and developers in translating policies to code. Even if Machine Learning (ML) models are used to find anomalies, they need to be regularly trained/updated to avoid becoming outdated. In an evolving environment, a ML model with outdated training might put at risk the organization it was supposed to defend. To overcome those issues, in this paper we propose an automated closed-loop process with three stages. The first stage focuses on obtaining the Decision Trees (DT) that classify anomalies. In the second stage, DTs are translated into security Policies as Code based on languages recognized by the Policy Engine (PE). In the last stage, the translated security policies feed the Policy Engines that enforce them by converting them into specific instruction sets. We also demonstrate the feasibility of the proposed framework, by presenting an example that encompasses the three stages of the closed-loop process. The proposed framework may integrate a broad spectrum of domains and use cases, being able for instance to support the decide and the act stages of the ETSI Zero-touch Network & Service Management (ZSM) framework.info:eu-repo/semantics/publishedVersio

Design and evaluation of acceleration strategies for speeding up the development of dialog applications

In this paper, we describe a complete development platform that features different innovative acceleration strategies, not included in any other current platform, that simplify and speed up the definition of the different elements required to design a spoken dialog service. The proposed accelerations are mainly based on using the information from the backend database schema and contents, as well as cumulative information produced throughout the different steps in the design. Thanks to these accelerations, the interaction between the designer and the platform is improved, and in most cases the design is reduced to simple confirmations of the “proposals” that the platform dynamically provides at each step. In addition, the platform provides several other accelerations such as configurable templates that can be used to define the different tasks in the service or the dialogs to obtain or show information to the user, automatic proposals for the best way to request slot contents from the user (i.e. using mixed-initiative forms or directed forms), an assistant that offers the set of more probable actions required to complete the definition of the different tasks in the application, or another assistant for solving specific modality details such as confirmations of user answers or how to present them the lists of retrieved results after querying the backend database. Additionally, the platform also allows the creation of speech grammars and prompts, database access functions, and the possibility of using mixed initiative and over-answering dialogs. In the paper we also describe in detail each assistant in the platform, emphasizing the different kind of methodologies followed to facilitate the design process at each one. Finally, we describe the results obtained in both a subjective and an objective evaluation with different designers that confirm the viability, usefulness, and functionality of the proposed accelerations. Thanks to the accelerations, the design time is reduced in more than 56% and the number of keystrokes by 84%