相关论文: Enhanced Bug Prediction in JavaScript Programs wit…

With the recent advances in AI programming assistants such as GitHub Copilot, programming is not limited to classical programming languages anymore--programming tasks can also be expressed and solved by end-users in natural text. Despite…

Context: Issue tracking systems are used to track and describe tasks in the development process, e.g., requested feature improvements or reported bugs. However, past research has shown that the reported issue types often do not match the…

Locating bugs is challenging but one of the most important activities in software development and maintenance phase because there are no certain rules to identify all types of bugs. Existing automatic bug localization tools use various…

Bugs are prevalent in software development. To improve software quality, bugs are filed using a bug tracking system. Properties of a reported bug would consist of a headline, description, project, product, component that is affected by the…

Context: Automated software defect prediction (SDP) methods are increasingly applied, often with the use of machine learning (ML) techniques. Yet, the existing ML-based approaches require manually extracted features, which are cumbersome,…

Testing plays an important role in securing the success of a software development project. Prior studies have demonstrated beneficial effects of applying acceptance testing within a Behavioural-Driven Development method. In this research,…

Identifying dependency call graphs of multilanguage software systems using static code analysis is challenging. The different languages used in developing today's systems often have different lexical, syntactical, and semantic rules that…

Improvements in the performance of computing systems, driven by Moore's Law, have transformed society. As such hardware-driven gains slow down, it becomes even more important for software developers to focus on performance and efficiency…

In games, and more generally in the field of software development, early detection of bugs is vital to maintain a high quality of the final product. Automated tests are a powerful tool that can catch a problem earlier in development by…

Currently, while software engineers write code for various modules, quite often, various types of errors - coding, logic, semantic, and others (most of which are not caught by compilation and other tools) get introduced. Some of these bugs…

Bug prediction has long been considered the "prince" of empirical software engineering research, and accordingly, a substantial body of work has focused on predicting bugs to enable early preventive actions. However, most existing studies…

Encoder-decoder models typically only employ words that are frequently used in the training corpus to reduce the computational costs and exclude noise. However, this vocabulary set may still include words that interfere with learning in…

Software security testing, particularly when enhanced with deep learning models, has become a powerful approach for improving software quality, enabling faster detection of known flaws in source code. However, many approaches miss post-fix…

Modern programming follows the continuous integration (CI) and continuous deployment (CD) approach rather than the traditional waterfall model. Even the development of modern programming languages uses the CI/CD approach to swiftly provide…

Binary code similarity comparison is a methodology for identifying similar or identical code fragments in binary programs. It is indispensable in fields of software engineering and security, which has many important applications (e.g.,…

During early optimization passes, compilers must make predictions for machine-dependent characteristics such as execution unit utilization, number of register spills, latency, throughput etc. to generate better code. Often a hand-written…

With an increasing number of value-flow properties to check, existing static program analysis still tends to have scalability issues when high precision is required. We observe that the key design flaw behind the scalability problem is that…

The use of large language models (LLMs) for automated code generation has emerged as a significant focus within AI research. As these pretrained models continue to evolve, their ability to understand and generate complex code structures has…

Recent studies have shown that bugs can be categorized into intrinsic and extrinsic types. Intrinsic bugs can be backtracked to specific changes in the version control system (VCS), while extrinsic bugs originate from external changes to…

Several applications of slicing require a program to be sliced with respect to more than one slicing criterion. Program specialization, parallelization and cohesion measurement are examples of such applications. These applications can…