Enbugging quiz is a format of programming exercises that let learners edit a given program so that it yields a designated error message. In order to formulate a quiz problem with less ambiguity and reasonable difficulty, one needs to consider many variants of a program and the produced errors. In this article, we propose two methods of assisting the problem formulation processes, namely a code minimization method that preserves error messages and an efficient method of searching alternative answers based on syntax-directed code generation. We also report the results of the application of the methods to the quiz problems that the authors composed for a university course in order to assess the effectiveness of the methods.

This paper introduces “Minissg,” a language extension for writing static website generation in JavaScript, with a focus on its design and implementation. Exploiting the modern JavaScript ecosystem, which includes functionalities for describing web contents on top of JavaScript's abstraction mechanisms, Minissg enables users to write not only procedures for automatic website generation but also webpage contents within a single JavaScript program. The program is built and executed to generate a website. By design, Minissg offers users all the features and developer experiences of modern JavaScript even within website authoring. Minissg is implemented as a Vite plugin comprising about 1,100 lines of code. Its conciseness and usefulness are achieved through design choices made from the perspective of developing a general-purpose programming language. This paper also presents an experience suggesting the descriptive power of using Minissg, which successfully translates about 8,700 lines of code from Astro into a codebase of nearly identical size within the proposed environment.

XStorm, an FRP language for small-scale embedded systems, allows us to concisely describe state-dependent behaviors based on the state transition model. However, when we use different sets of peripheral devices depending on states, device management, such as switching power modes, should be implemented in a driver code in C. This would result in bugs as inconsistency between the state in the XStorm program and that in the driver code cannot be detected. In this research, we extend XStorm's state hook model to express modes of peripherals that depend on states. By the extension, the language manages modes of peripherals, and thus the inconsistency is statically avoided.

In recent years, there has been a number of studies on automatic program repair (APR) techniques to reduce the burden on developers in fixing defects. The quality of patches generated by APR techniques is verified by passing test cases to determine if the patches are correct. However, coding standards after the patches are applied have not been taken into account in designing APR techniques. In this paper, we analyze the impact of automatically-generated patches (APR patches) on coding standard violations. As a result of analyzing three OSS projects, we found that APR techniques increased the number of coding standard violations by about 40% regardless of the types of coding standards (RQ1). We also found that most of coding standard violations generated by the APR techniques were minor but about 9% to 10% of the violations had an impact on the readability of source code(RQ2). Forthermore, we found that APR techniques that generate patches in a similar manner tend to generate similar cording standard violations(RQ3).

In recent years, self-learning support systems, such as online judging systems, have attracted the attention of programming students due to the high demand for skilled programmers. An online judging system requires various test data to test the programs submitted to it automatically. However, it is not easy to prepare a wide variety of test data while considering different programs to be judged. Although the symbolic execution technique aids in generating test data from a program under test, its test data generation focuses only on the coverage of the given program's control flow and cannot care for different programs with different control flows. This paper proposes a novel method using the mutation technique with the symbolic execution technique to achieve better test data generation. The empirical study using 21,240 C programs submitted to Codeforces, an online judging system, shows that the proposed methods can generate test data useful for the accurate and efficient testing of submitted programs.

This paper proposes MusicCommentVisualizer, an interface that enables music recommendations (automatic playlist generation) and music appreciation suited to the user's situation and emotions while visualizing YouTube comments on music videos. Although there have been studies on music recommendation and interactive systems for listening to music suited to the user's situation and emotions, there have been no studies that consider both situation and emotion on the basis of comments on music videos. The user's situation and emotions influence their music preferences when they are listening to music. Thus, it is important to consider both at the same time in order to offer a variety of music recommendations and forms of appreciation. MusicCommentVisualizer automatically extracts words from comments on music videos and classifies them as to their situation and emotion. Then, it visualizes them as clickable frequency distributions that can be used interactively to select situations and emotions. It can also generate music playlists based on the situation and emotion selected by the user from the distribution and display comments that explain why these songs were recommended.

This paper investigates a new method for adjusting game skills in the game of Hyakunin Isshu Karuta. We implemented a system that allows players to experience the commonly used rule sets of “Chirashi-dori" and “Kyogi Karuta" within a VR space. Furthermore, considering that a part of the process of taking cards in the Hyakunin Isshu Karuta game can be seen as a so-called pointing task, we conducted a mathematical model analysis using Fitts' law on data obtained from subject experiments. As a result, it was possible to accurately predict the impact on the time required to take cards by changing the distance to the cards, the size of the hand, and the size of the cards within the VR space. Additionally, we extracted the range that players felt was appropriate for various parameter changes during this process. These results suggest the effectiveness of a method that controls the time required to take cards by appropriately changing the distance to the cards, the size of the hand, and the size of the cards within a VR space, thereby adjusting the skill gaps between players. We also discussed the impact of such changes on the perception of the player themselves and their opponents.