Enhancing Binary Code Comment Quality Classification: Integrating Generative AI for Improved Accuracy

This report focuses on enhancing a binary code comment quality classification model by integrating generated code and comment pairs, to improve model accuracy. The dataset comprises 9048 pairs of code and comments written in the C programming language, each annotated as "Useful" or "Not Useful." Additionally, code and comment pairs are generated using a Large Language Model Architecture, and these generated pairs are labeled to indicate their utility. The outcome of this effort consists of two classification models: one utilizing the original dataset and another incorporating the augmented dataset with the newly generated code comment pairs and labels.Comment: 11 pages, 2 figures, 2 tables, Has been accepted for the Information Retrieval in Software Engineering track at Forum for Information Retrieval Evaluation 202

Pemetaan Secara Sistematis Pada Metrik Kualitas Perangkat Lunak

. Software quality assurance is one method to increase quality of software. Improvement of software quality can be measured with software quality metric. Software quality metrics are part of software quality measurement model. Currently software quality models have a very diverse types, so that software quality metrics become increasingly diverse. The various types of metrics to measure the quality of software create proper metrics selection issues to fit the desired quality measurement parameters. Another problem is the validation need to be performed on these metrics in order to obtain objective and valid results. In this paper, a systematic mapping of the software quality metric is conducted in the last nine years. This paper brings up issues in software quality metrics that can be used by other researchers. Furthermore, current trends are introduced and discussed

Speculative Analysis for Quality Assessment of Code Comments

Previous studies have shown that high-quality code comments assist developers in program comprehension and maintenance tasks. However, the semi-structured nature of comments, unclear conventions for writing good comments, and the lack of quality assessment tools for all aspects of comments make their evaluation and maintenance a non-trivial problem. To achieve high-quality comments, we need a deeper understanding of code comment characteristics and the practices developers follow. In this thesis, we approach the problem of assessing comment quality from three different perspectives: what developers ask about commenting practices, what they write in comments, and how researchers support them in assessing comment quality. Our preliminary findings show that developers embed various kinds of information in class comments across programming languages. Still, they face problems in locating relevant guidelines to write consistent and informative comments, verifying the adherence of their comments to the guidelines, and evaluating the overall state of comment quality. To help developers and researchers in building comment quality assessment tools, we provide: (i) an empirically validated taxonomy of comment convention-related questions from various community forums, (ii) an empirically validated taxonomy of comment information types from various programming languages, (iii) a language-independent approach to automatically identify the information types, and (iv) a comment quality taxonomy prepared from a systematic literature review.Comment: 5 pages, 1 figure, conferenc

From voice to knowledge: A proposal for a voice annotation system to support collaborative engineering design processes

This paper describes a novel voice interaction mechanism for capturing and managing design knowledge within a collaborative Computer-Aided Design (CAD) environment. We present a software module for speech recognition that integrates with a CAD application to allow the automatic creation of textual annotations in a 3D model directly from voice data. Audio is transcribed automatically, resulting in a textual note that is searchable and available to other users via a Product Data Management (PDM) system, providing an intuitive mechanism to document modeling processes and design knowledge. The system consists of three functional blocks: (1) audio recording, (2) speech recognition, and (3) query management against a cloud-based service. In this paper, we justify the need for our system from a human-computer interaction standpoint and discuss the rationale of its design and implementation in the context of collaborative design communication. Finally, we discuss some application spaces that demonstrate the capability of voice annotations for capturing knowledge

End-user satisfaction as an impact of the system quality, information quality, and top management support, upon the perceived usefulness of technology utilization

The utilization of Accounting Information System (AIS) by the small, medium, and micro enterprises (SMEs) at present is apparently at the minimum level if not to mention the integrated operation. This study attempts to fathom and analyse, first, the impact of subsequently the system quality, the information quality, the top management support upon the perceived usefulness. Second, the effect of the system quality, the information quality, and the top management support on the end-user information satisfaction. Third, how the perceived usefulness affect the end-user information satisfaction. Fourth, to analyze the effect of the system quality, the information quality, and the top management support on end-user information satisfaction via the perceived usefulness. The study observed the designated SMEs managers in a chosen area of targeted location in East Java, Indonesia. The structural equation modelling was employed to study the effect of those variables under study, namely the system quality, information quality, top management support on the end-user information satisfaction through the perceived usefulness. The results revealed that the system quality, the information quality, as well as the top management support proven to be affecting the designated SMEs perceived usefulness. Among those variables under study, it was proved that the system quality, information quality, top management support influence on the end-user information satisfaction. However, the perceived usefulness is an intervening variable that can mediate the effect of system quality, the information quality, the top management support on the end-user information satisfaction