Related papers: Estimation and Prediction of technical debt: a pro…
[Context] Technical debt (TD) in machine learning (ML) systems, much like its counterpart in software engineering (SE), holds the potential to lead to future rework, posing risks to productivity, quality, and team morale. Despite growing…
Estimation is one of the most critical areas in software project management life cycle, which is still evolving and less matured as compared to many other industries like construction, manufacturing etc. Originally the word estimation, in…
The development of Machine Learning (ML)- and, more recently, of Deep Learning (DL)-intensive systems requires suitable choices, e.g., in terms of technology, algorithms, and hyper-parameters. Such choices depend on developers' experience,…
Test-driven development (TDD) is a programming technique in which the tests are written prior to the source code. It is proposed that TDD is one of the most fundamental practices enabling the development of software in an agile and…
Agentic AI systems combine probabilistic reasoning with delegated action through tools, context, memory, orchestration, and external workflow integration. This note develops a formal and managerially usable model that distinguishes Agentic…
Objective. In this work, we report the experience of a Finnish SME in managing Technical Debt (TD), investigating the most common types of TD they faced in the past, their causes, and their effects. Method. We set up a focus group in the…
The rapid adoption of Deep Learning (DL)-enabled systems has revolutionized software development, driving innovation across various domains. However, these systems also introduce unique challenges, particularly in maintaining software…
Architectural technical debt (ATD) represents trade-offs in software architecture that accelerate initial development but create long-term maintenance challenges. ATD, in particular when self-admitted, impacts the foundational structure of…
The software industry is successful, if it can draw the complete attention of the customers towards it. This is achievable if the organization can produce a high quality product. To identify a product to be of high quality, it should be…
With the increasing reliance on software and automation nowadays, tight deadlines, limited resources, and prioritization of functionality over security can lead to insecure coding practices. When not handled properly, these constraints…
Defect prevention is the most vital but habitually neglected facet of software quality assurance in any project. If functional at all stages of software development, it can condense the time, overheads and wherewithal entailed to engineer a…
Self-admitted technical debt (SATD) refers to comments in which developers explicitly acknowledge code issues, workarounds, or suboptimal solutions. SATD is known to significantly increase software maintenance effort. While extensive…
Bankruptcy prediction is an important research area that heavily relies on data science. It aims to help investors, managers, and regulators better understand the operational status of corporations and predict potential financial risks in…
A vigorous and growing set of technical debt analysis tools have been developed in recent years -- both research tools and industrial products -- such as Structure 101, SonarQube, and DV8. Each of these tools identifies problematic files…
Software design debt aims to elucidate the rectification attempts of the present design flaws and studies the influence of those to the cost and time of the software. Design smells are a key cause of incurring design debt. Although the…
Keeping track of and managing Self-Admitted Technical Debts (SATDs) are important to maintaining a healthy software project. This requires much time and effort from human experts to identify the SATDs manually. The current automated…
Effort estimation is a key factor for software project success, defined as delivering software of agreed quality and functionality within schedule and budget. Traditionally, effort estimation has been used for planning and tracking project…
Background: To adequately attend to non-functional requirements (NFRs), they must be documented; otherwise, developers would not know about their existence. However, the documentation of NFRs may be subject to Technical Debt and Waste, as…
Technical Debt analysis is increasing in popularity as nowadays researchers and industry are adopting various tools for static code analysis to evaluate the quality of their code. Despite this, empirical studies on software projects are…
Carbon emissions significantly contribute to climate change, and carbon credits have emerged as a key tool for mitigating environmental damage and helping organizations manage their carbon footprint. Despite their growing importance across…