A5019105285- Software Engineering Research
- Software Reliability and Analysis Research
- Software Engineering Techniques and Practices
- Software System Performance and Reliability
- Advanced Software Engineering Methodologies
- Technology Assessment and Management
- ERP Systems Implementation and Impact
- Healthcare Policy and Management
- Software Testing and Debugging Techniques
- Advanced Malware Detection Techniques
- Stock Market Forecasting Methods
- Advanced Data Storage Technologies
- Energy Load and Power Forecasting
- Distributed and Parallel Computing Systems
- Service-Oriented Architecture and Web Services
- Financial Reporting and XBRL
- Credit Risk and Financial Regulations
- Building Energy and Comfort Optimization
- Economic and Technological Systems Analysis
- Open Source Software Innovations
- Scientific Computing and Data Management
- Power Systems and Renewable Energy
- Cloud Computing and Resource Management
- Economic and Technological Developments in Russia
- Advanced Statistical Process Monitoring
Tampere University
2019-2024
Different tools adopt different terms, metrics, and ways to identify measure technical debt. We attempt clarify the situation by comparing features popularity of debt measurement analyzing existing empirical evidence on their validity.
Technical Debt analysis is increasing in popularity as nowadays researchers and industry are adopting various tools for static code to evaluate the quality of their code. Despite this, empirical studies on software projects expensive because time needed analyze projects. In addition, results difficult compare commonly consider different this work, we propose Dataset, a curated set project measurement data from 33 Java Apache Software Foundation. analyzed all commits separately defined frames...
Empirical Standards are natural-language models of a scientific community's expectations for specific kind study (e.g. questionnaire survey). The ACM SIGSOFT Paper and Peer Review Quality Initiative generated empirical standards research methods commonly used in software engineering. These living documents, which should be continuously revised to reflect evolving consensus around best practices, will improve quality make peer review more effective, reliable, transparent fair.
Background. Companies commonly invest major effort into removing, respectively not introducing, technical debt issues detected by static analysis tools such as SonarQube, Cast, or Coverity. These classify categories according to severity, and developers pay attention introducing with a high level of severity that could generate bugs make software maintenance more difficult. Objective. In this work, we aim understand the diffuseness Technical Debt (TD) speed which remove them from code if...
[Context] The popularity of tools for software quality analysis has increased over the years, with special attention to that calculate technical debt based on violations a set rules. SonarQube is one most used and provides an estimation time needed remediate debt. However, practitioners are still skeptical about accuracy its remediation estimation. [Objective] In this paper, we analyze 15 open source Java projects. [Method] We designed conducted case study where asked 65 novice developers...
Pull requests are a common practice for making contributions and reviewing them in both open-source industrial contexts. Our goal is to understand whether quality flaws such as code smells, anti-patterns, security vulnerabilities, coding style violations pull request's affect the chance of its acceptance when reviewed by maintainer project. We conducted case study among 28 Java projects, analyzing presence 4.7 M 36 K requests. analyzed further correlations applying logistic regression six...
Developers use Static Analysis Tools (SATs) to control for potential quality issues in source code, including defects and technical debt. Tool vendors have devised quite a number of tools, which makes it harder practitioners select the most suitable one their needs. To better support developers, researchers been conducting several studies on SATs favor understanding actual capabilities. Despite work done so far, there is still lack knowledge regarding (1) what agreement, (2) precision...
Background. Developers use Static Analysis Tools to control for potential quality issues in source code. Tool vendors have devised quite a number of tools, which makes it harder practitioners select the most suitable one their needs. To better support developers, researchers been conducting several studies on SATs favor understanding actual capabilities. Aims. Despite work done so far, there is still lack knowledge regarding (1) what agreement, and (2) precision recommendations. We aim at...
Background. The need to release our products under tough time constraints has required us take shortcuts during the implementation of and postpone correct implementation, thereby accumulating Technical Debt. Objective. In this work, we report experience a Finnish SME in managing Debt (TD), investigating most common types TD they faced past, their causes, effects. Method. We set up focus group case-company, involving different roles. Results. results showed that significant company stems from...
Predicting Technical Debt has become a popular research niche in recent software engineering literature. However, there is no consistent approach yet that succeeds entirely capturing the nature of this type data. We applied each technique on dataset consisting commit data total 28 Java projects. predicted future values SQALE index to evaluate their predictive performance. Using these techniques we confirmed power them with same aim investigate further time-dependent other types validate...
Background. Several recent software engineering studies use data mined from the version control systems adopted by different projects. However, inspecting and statistical methods used in those reveals several problems with current approach, mainly related to dependent nature of data. Objective. We analyzed time-dependent at commit level, propose an alternative approach based on time series analysis. Method. identified tests designed for analysis a technique model data, similarly what is done...
Background: Starting from the 1960s, practitioners and researchers have looked for ways to empirically investigate new technologies such as inspecting effectiveness of methods, tools, or practices. With this purpose, empirical software engineering domain started identify different borrowing them various domains medicine, biology, psychology. Nowadays, a variety methods are commonly applied in engineering, ranging controlled quasi-controlled experiments case studies, systematic literature...
This paper presents the design and applications of a data collection supplementary control platform developed for modern office building. The challenges possibilities such are discussed. is needed to aggregate utilize available controls in buildings. comprises collector at edge collecting, filtering buffering rapid actions, an IoT back end analyses visualizations. realized computing unit while cloud based may be utilized slow responses energy management. Data collected from internal (e.g....
Background: Technical Debt is a consolidated notion in software engineering research and practice. However, the estimation of its impact (interest debt) still imprecise requires heavy empirical experimental inquiry. Objective: We aim at developing data-driven approach to calculate interest terms delays resolving affected tasks.Method: conducted case study estimate by analyzing association with lead time variation related Jira issues.Results: Data-driven approaches could significantly change...
Background: Logging is an important part of modern software projects; logs are used in several tasks such as debugging and testing. Due to the complex nature logging, it remains a difficult task with pitfalls that could have serious consequences. Several other domains engineering mitigated threats by identifying early signs more issues, i.e., "smells". However, this concept not yet properly defined for logging. Objective: The goal study create taxonomy log smells can help developers write...
Code Technical Debt prediction has become a popular research niche in recent software engineering literature. is an important metric projects as it measures professionals' effort to clean the code. Therefore, predicting its future behavior becomes crucial task. However, no well-defined and consistent approach can completely capture features that impact evolution of Debt. The goal this study evaluate considering time-dependent techniques well seasonal effects temporal data performance within...
Background. Most Mining Software Repositories (MSR) studies cannot obtain causal relations because they are not controlled experiments. The use of cohort as defined in epidemiology could help to overcome this shortcoming.
Background. Pull requests are a common practice for contributing and reviewing contributions, employed both in open-source industrial contexts. One of the main goals code reviews is to find defects code, allowing project maintainers easily integrate external contributions into discuss contributions. Objective. The goal this paper understand whether quality actually considered when pull accepted. Specifically, we aim at understanding issues such as smells, antipatterns, coding style...
Background. Starting from the 1960s, practitioners and researchers have looked for ways to empirically investigate new technologies such as inspecting effectiveness of methods, tools, or practices. With this purpose, empirical software engineering domain started identify different borrowing them various domains medicine, biology, psychology. Nowadays, a variety methods are commonly applied in engineering, ranging controlled quasi-controlled experiments case studies, systematic literature...