相关论文: Object-Oriented Program Comprehension: Effect of E…

Affects---emotions and moods---have an impact on cognitive activities and the working performance of individuals. Development tasks are undertaken through cognitive processes, yet software engineering research lacks theory on affects and…

Literature and intuition suggest that a developer's intelligence and personality have an impact on their performance in comprehending source code. Researchers made this suggestion in the past when discussing threats to validity of their…

To answer a question, language models often need to integrate prior knowledge learned during pretraining and new information presented in context. We hypothesize that models perform this integration in a predictable way across different…

The comprehension of business process models is crucial for enterprises. Prior research has shown that children as well as adolescents perceive and interpret graphical representations in a different manner compared to grown-ups. To evaluate…

Objectives: This study aims to investigate the readability and understandability of bitwise operators in programming, with the main hypothesis that there will be a difference in the performance metrics (response time and error rate) between…

Context: Forgetting is defined as a gradual process of losing information. Even though there are many studies demonstrating the effect of forgetting in software development, to the best of our knowledge, no study explores the impact of…

Programmers' mental models represent their knowledge and understanding of programs, programming concepts, and programming in general. They guide programmers' work and influence their task performance. Understanding mental models is…

This study examined the impact of Code.org's block-based coding curriculum on primary school students' computational thinking, motivation, attitudes, and academic performance. Twenty students participated, and a range of tools was used: the…

Program representation learning is a fundamental task in software engineering applications. With the availability of "big code" and the development of deep learning techniques, various program representation learning models have been…

Context: Various approaches aim to support program comprehension by automatically detecting algorithms in source code. However, no empirical evaluations of their helpfulness have been performed. Objective: To empirically evaluate how…

The development of data science expertise requires tacit, process-oriented skills that are difficult to teach directly. This study addresses the resulting challenge of empirically understanding how the problem-solving processes of experts…

Programming by Example (PBE) is the task of inducing computer programs from input-output examples. It can be seen as a type of machine learning where the hypothesis space is the set of legal programs in some programming language. Recent…

Program tracing, or mentally simulating a program on concrete inputs, is an important part of general program comprehension. Programs involve many kinds of virtual state that must be held in memory, such as variable/value pairs and a call…

This work presents insights about the long-term effects and retention rates of knowledge acquired within MOOCs. In 2015 and 2017, we conducted two introductory MOOCs on object-oriented programming in Java with each over 10,000 registered…

Transitioning from block-based programming to text-based programming environments can be challenging as it requires students to learn new programming language concepts. In this paper, we identify and classify the issues encountered when…

We focus on the task of reasoning over paragraph effects in situation, which requires a model to understand the cause and effect described in a background paragraph, and apply the knowledge to a novel situation. Existing works ignore the…

Software change is the basic task of software evolution and maintenance. Phased Model for Software Change (PMSC) is a process model for software changes that localize in the code. It consists of several phases that cover both program…

This paper presents a study aiming to analyse the design strategies of experts in object-oriented programming. We report an experiment conducted with four experts. Each subject solved three problems. Our results show that three strategies…

Concept-based interpretability methods aim to explain deep neural network model predictions using a predefined set of semantic concepts. These methods evaluate a trained model on a new, "probe" dataset and correlate model predictions with…

In recent years, deep learning techniques have been developed to improve the performance of program synthesis from input-output examples. Albeit its significant progress, the programs that can be synthesized by state-of-the-art approaches…