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Background. Software companies need to manage and refactor Technical Debt issues. Therefore, it is necessary to understand if and when refactoring Technical Debt should be prioritized with respect to developing features or fixing bugs.…

Over the last decades, a considerable amount of empirical knowledge about the efficiency of defect-detection techniques has been accumulated. Also a few surveys have summarised those studies with different focuses, usually for a specific…

Large Language Models (LLMs) are gaining popularity among software engineers. A crucial aspect of developing effective code generation LLMs is to evaluate these models using a robust benchmark. Evaluation benchmarks with quality issues can…

Vibe Coding (VC) is a form of software development assisted by generative AI, in which developers describe the intended functionality or logic via natural language prompts, and the AI system generates the corresponding source code. VC can…

To complete tasks faster, developers often have to sacrifice the quality of the software. Such compromised practice results in the increasing burden to developers in future development. The metaphor, technical debt, describes such practice.…

Large Language Models (LLMs) have demonstrated exceptional code generation capabilities, yet their token-level mechanisms remain underexplored, particularly in compressed models. Through systematic analysis of programming language token…

Generating software from abstract models is a prime activity in model-drivenengineering. Adaptable and extendable code generators are important to address changing technologies as well as user needs. However, theyare less established, as…

Code cloning is not only assumed to inflate maintenance costs but also considered defect-prone as inconsistent changes to code duplicates can lead to unexpected behavior. Consequently, the identification of duplicated code, clone detection,…

Aim: In contrast to studies of defects found during code review, we aim to clarify whether code reviews measures can explain the prevalence of post-release defects. Method: We replicate a study by McIntoshet. al that uses additive…

Machine learning models are essential tools in various domains, but their performance can degrade over time due to changes in data distribution or other factors. On one hand, detecting and addressing such degradations is crucial for…

Technical debt (TD) is a metaphor that is used to communicate the consequences of poor software development practices to non-technical stakeholders. In recent years, it has gained significant attention in agile software development (ASD).…

Code completion is widely used by software developers to provide coding suggestions given a partially written code snippet. Apart from the traditional code completion methods, which only support single token completion at minimal positions,…

Software quality is considered as one of the most important challenges in software engineering. It has many dimensions which differ from users' point of view that depend on their requirements. Therefore, those dimensions lead to difficulty…

Maintainability is a key quality attribute of successful software systems. However, its management in practice is still problematic. Currently, there is no comprehensive basis for assessing and improving the maintainability of software…

Technical Debt, considered by many to be the 'silent killer' of software projects, has undeniably become part of the everyday vocabulary of software engineers. We know it compromises the internal quality of a system, either deliberately or…

Code Smell, similar to a bad smell, is a surface indication of something tainted but in terms of software writing practices. This metric is an indication of a deeper problem lies within the code and is associated with an issue which is…

One of the prerequisites of any organization is an unvarying sustainability in the dynamic and competitive industrial environment. Development of high quality software is therefore an inevitable constraint of any software industry. Defect…

Technical debt (TD) is a metaphor for code-related problems that arise as a result of prioritizing speedy delivery over perfect code. Given that the reduction of TDs can have long-term positive impact in the software engineering life-cycle…

Performance models are well-known instruments to understand the scaling behavior of parallel applications. They express how performance changes as key execution parameters, such as the number of processes or the size of the input problem,…

Context: Technical Debt (TD) can be paid back either by those that incurred it or by others. We call the former self-fixed TD, and it can be particularly effective, as developers are experts in their own code and are well-suited to fix the…