相关论文: An architectural technical debt index based on mac…

Machine learning (ML) codebases face unprecedented challenges in maintaining code quality and sustainability as their complexity grows exponentially. While traditional code smell detection tools exist, they fail to address ML-specific…

Code smells represent sub-optimal implementation choices applied by developers when evolving software systems. The negative impact of code smells has been widely investigated in the past: besides developers' productivity and ability to…

Technical debt (TD) refers to suboptimal choices during software development that achieve short-term goals at the expense of long-term quality. Although developers often informally discuss TD, the concept has not yet crystalized into a…

A code smell is a surface indicator of an inherent problem in the system, most often due to deviation from standard coding practices on the developers part during the development phase. Studies observe that code smells made the code more…

Community smells appear in sub-optimal software development community structures, causing unforeseen additional project costs, e.g., lower productivity and more technical debt. Previous studies analyzed and predicted community smells in the…

The learning and usage of an API is supported by official documentation. Like source code, API documentation is itself a software product. Several research results show that bad design in API documentation can make the reuse of API features…

Understanding and effectively managing Technical Debt (TD) remains a vital challenge in software engineering. While many studies on code-level TD have been published, few illustrate the business impact of low-quality source code. In this…

Potential benefits such as agile service delivery have led many companies to deliver their business capabilities through microservices. Bad smells are however always around the corner, as witnessed by the considerable body of literature…

Technical debt is a metaphor indicating sub-optimal solutions implemented for short-term benefits by sacrificing the long-term maintainability and evolvability of software. A special type of technical debt is explicitly admitted by software…

Balancing the management of technical debt within recommender systems requires effectively juggling the introduction of new features with the ongoing maintenance and enhancement of the current system. Within the realm of recommender…

Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how…

Technical debt (TD) refers to delayed tasks and immature artifacts that may bring short-term benefits but incur extra costs of change during maintenance and evolution in the long term. TD has been extensively studied in the past decade, and…

In this paper, we present a tertiary systematic literature review of previous surveys, secondary systematic literature reviews, and systematic mappings. We identify the main observations (what we know) and challenges (what we do not know)…

Bad requirements quality can cause expensive consequences during the software development lifecycle, especially if iterations are long and feedback comes late. %-- the faster a problem is found, the cheaper it is to fix. This makes explicit…

Similarly to production code, code smells also occur in test code, where they are called test smells. Test smells have a detrimental effect not only on test code but also on the production code that is being tested. To date, the majority of…

Advances in AI have led to new types of technical debt in software engineering projects. AI-based competition platforms face challenges due to rapid prototyping and a lack of adherence to software engineering principles by participants,…

Cognitive biases exert a significant influence on human thinking and decision-making. In order to identify how they influence the occurrence of architectural technical debt, a series of semi-structured interviews with software architects…

The growth of Python adoption across diverse domains has led to increasingly complex codebases, presenting challenges in maintaining code quality. While numerous tools attempt to address these challenges, they often fall short in providing…

Context: Software specifications are usually written in natural language and may suffer from imprecision, ambiguity, and other quality issues, called thereafter, requirement smells. Requirement smells can hinder the development of a project…

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.…