Understanding automated and human-based technical debt identification approaches-a two-phase study

Context: The technical debt (TD) concept inspires the development of useful methods and tools that support TD identification and management. However, there is a lack of evidence on how different TD identification tools could be complementary and, also, how human-based identification compares with them. Objective: To understand how to effectively elicit TD from humans, to investigate several types of tools for TD identification, and to understand the developers’ point of view about TD indicators and items reported by tools. Method: We asked developers to identify TD items from a real software project. We also collected the output of three tools to automatically identify TD and compared the results in terms of their locations in the source code. Then, we collected developers’ opinions on the identification process through a focus group. Results: Aggregation seems to be an appropriate way to combine TD reported by developers. The tools used cannot help in identifying many important TD types, so involving humans is necessary. Developers reported that the tools would help them to identify TD faster or more accurately and that project priorities and current development activities are important to be considered together, along with the values of principal and interest, when deciding to pay off a debt. Conclusion: This work contributes to the TD landscape, which depicts an understanding between different TD types and how they are best discovered

On The Impact of Passive Voice Requirements on Domain Modelling

Context: The requirements specification is a central arte- fact in the software engineering (SE) process, and its quality (might) influence downstream activities like implementation or testing. One quality defect that is often mentioned in standards is the use of passive voice. However, the con- sequences of this defect are still unclear. Goal: We need to understand whether the use of passive voice in requirements has an influence on other activities in SE. In this work we focus on domain modelling. Method: We designed an experiment, in which we ask students to draw a domain model from a given set of requirements written in active or passive voice. We compared the completeness of the resulting domain model by counting the number of missing actors, domain objects and their associations with respect to a specified solution. Results: While we could not see a difference in the number of missing actors and objects, participants which received passive sentences missed almost twice the associations. Conclusion: Our experiment indicates that, against common knowledge, actors and objects in a requirement can often be understood from the context. However, the study also shows that passive sentences complicate understanding how certain domain concepts are interconnected

A Survey on What Developers Think About Testing

Software is infamous for its poor quality and frequent occurrence of bugs. While there is no doubt that thorough testing is an appropriate answer to ensure sufficient quality, the poor state of software generally suggests that developers may not always engage as thoroughly with testing as they should. This observation aligns with the prevailing belief that developers simply do not like writing tests. In order to determine the truth of this belief, we conducted a comprehensive survey with 21 questions aimed at (1) assessing developers' current engagement with testing and (2) identifying factors influencing their inclination toward testing; that is, whether they would actually like to test more but are inhibited by their work environment, or whether they would really prefer to test even less if given the choice. Drawing on 284 responses from professional software developers, we uncover reasons that positively and negatively impact developers' motivation to test. Notably, reasons for motivation to write more tests encompass not only a general pursuit of software quality but also personal satisfaction. However, developers nevertheless perceive testing as mundane and tend to prioritize other tasks. One approach emerging from the responses to mitigate these negative factors is by providing better recognition for developers' testing efforts

Applying Scriptless Test Automation on Web Applications from the Financial Sector

[EN] This industry showcase presents experiences on application of testar, an open source tool for scriptless testing through graphical user interface (GUI), to the web applications of Kuveyt T¿urk Participation Bank in Turkey. Kuveyt T¿urk Bank uses Selenium and Appium for regression testing of mobile and internet banking, but the maintenance cost of the test scripts is increasing day by day. Therefore, scriptless GUI testing with testar was evaluated. To provide better support for testing web-based applications, testar was extended with Selenium WebDriver integration, JavaScript support, and other new features. Results show that testar detects GUI elements much better after the improvements, and it was able to find 2 relevant errors that were not identified by existing scripted test cases.This work has been partially funded by ITEA3 TESTOMAT Project, ITEA3 IVVES project7 and EU H2020 DECODER projecAho, P.; Buijs, G.; Akin, A.; Senturk, S.; Pastor-Ricós, F.; De Gouw, S.; Vos, TE. (2021). Applying Scriptless Test Automation on Web Applications from the Financial Sector. SISTEDES. 1-4. http://hdl.handle.net/10251/178254S1

A systematic literature review of open data quality in practice

Context: The main objective of open data initiatives is to make information freely available through easily accessible mechanisms and facilitate exploitation. In practice openness should be accompanied with a certain level of trustwor- thiness or guarantees about the quality of data. Traditional data quality is a thoroughly researched field with several benchmarks and frameworks to grasp its dimensions. However, quality assessment in open data is a complicated process as it consists of stakeholders, evaluation of datasets as well as the publishing platform. Objective: In this work, we aim to identify and synthesize various features of open data quality approaches in practice. We applied thematic synthesis to identify the most relevant research problems and quality assessment methodologies. Method: We undertook a systematic literature review to summarize the state of the art on open data quality. The review process starts by developing the review protocol in which all steps, research questions, inclusion and exclusion criteria and analysis procedures are included. The search strategy retrieved 9323 publications from four scientific digital libraries. The selected papers were published between 2005 and 2015. Finally, through a discussion between the authors, 63 paper were included in the final set of selected papers. Results: Open data quality, in general, is a broad concept, and it could apply to multiple areas. There are many quality issues concerning open data hindering their actual usage for real-world applications. The main ones are unstruc- tured metadata, heterogeneity of data formats, lack of accuracy, incompleteness and lack of validation techniques. Furthermore, we collected the existing quality methodologies from selected papers and synthesized under a unifying classification schema. Also, a list of quality dimensions and metrics from selected paper is reported. Conclusion: In this research, we provided an overview of the methods related to open data quality, using the instru- ment of systematic literature reviews. Open data quality methodologies vary depending on the application domain. Moreover, the majority of studies focus on satisfying specific quality criteria. With metrics based on generalized data attributes a platform can be created to evaluate all possible open dataset. Also, the lack of methodology validation remains a major problem. Studies should focus on validation techniques

Measuring the Use of the Active and Assisted Living Prototype CARIMO for Home Care Service Users: Evaluation Framework and Results

To address the challenges of aging societies, various information and communication technology (ICT)-based systems for older people have been developed in recent years. Currently, the evaluation of these so-called active and assisted living (AAL) systems usually focuses on the analyses of usability and acceptance, while some also assess their impact. Little is known about the actual take-up of these assistive technologies. This paper presents a framework for measuring the take-up by analyzing the actual usage of AAL systems. This evaluation framework covers detailed information regarding the entire process including usage data logging, data preparation, and usage data analysis. We applied the framework on the AAL prototype CARIMO for measuring its take-up during an eight-month field trial in Austria and Italy. The framework was designed to guide systematic, comparable, and reproducible usage data evaluation in the AAL field; however, the general applicability of the framework has yet to be validated

Towards a hybrid testing process unifying exploratory testing and scripted testing

CONTEXT Given the current state of the art in research, practitioners are faced with the challenge of choosing scripted testing (ST) or exploratory testing (ET). OBJECTIVE This study aims at systematically incorporating strengths of ET and ST in a hybrid testing process to overcome the weaknesses of each. METHOD We utilized systematic review and practitioner interviews to identify strengths and weaknesses of ET and ST. Strengths of ET were mapped to weaknesses of ST and vice versa. Noblit and Hare's lines-ofargument method was used for data analysis. The results of the mapping were used as input to codesign a hybrid process with experienced practitioners. RESULTS We found a clear need to create a hybrid process as follows: (i) both ST and ET provide strengths and weaknesses, and these depend on some particular conditions, which prevents preference of one approach to another; and (ii) the mapping showed that it is possible to address the weaknesses in one process by the strengths of the other in a hybrid form. With the input from literature and industry experts, a flexible and iterative hybrid process was designed. CONCLUSIONS Practitioners can clearly benefit from using a hybrid process given the mapping of advantages and disadvantage

Evolution of technical debt remediation in Python: A case study on the Apache Software Ecosystem

In recent years, the evolution of software ecosystems and the detection of technical debt received significant attention by researchers from both industry and academia. While a few studies that analyze various aspects of technical debt evolution already exist, to the best of our knowledge, there is no large-scale study that focuses on the remediation of technical debt over time in Python projects -- i.e., one of the most popular programming languages at the moment. In this paper, we analyze the evolution of technical debt in 44 Python open-source software projects belonging to the Apache Software Foundation. We focus on the type and amount of technical debt that is paid back. The study required the mining of over 60K commits, detailed code analysis on 3.7K system versions, and the analysis of almost 43K fixed issues. The findings show that most of the repayment effort goes into testing, documentation, complexity and duplication removal. Moreover, more than half of the Python technical debt in the ecosystem is short-term being repaid in less than two months. In particular, the observations that a minority of rules account for the majority of issues fixed and spent effort, suggest that addressing those kinds of debt in the future is important for research and practice

EMPIRICAL CHARACTERIZATION OF SOFTWARE QUALITY

The research topic focuses on the characterization of software quality considering the main software elements such as people, process and product. Many attributes (size, language, testing techniques etc.) probably could have an effect on the quality of software. In this thesis we aim to understand the impact of attributes of three P’s (people, product, process) on the quality of software by empirical means. Software quality can be interpreted in many ways, such as customer satisfaction, stability and defects etc. In this thesis we adopt ‘defect density’ as a quality measure. Therefore the research focus on the empirical evidences of the impact of attributes of the three P’s on the software defect density. For this reason empirical research methods (systematic literature reviews, case studies, and interviews) are utilized to collect empirical evidence. Each of this research method helps to extract the empirical evidences of the object under study and for data analysis statistical methods are used. Considering the product attributes, we have studied the size, language, development mode, age, complexity, module structure, module dependency, and module quality and their impact on project quality. Considering the process attributes, we have studied the process maturity and structure, and their impact on the project quality. Considering the people attributes, we have studied the experience and capability, and their impact on the project quality. Moreover, in the process category, we have studied the impact of one testing approach called ‘exploratory testing’ and its impact on the quality of software. Exploratory testing is a widely used software-testing practice and means simultaneous learning, test design, and test execution. We have analyzed the exploratory testing weaknesses, and proposed a hybrid testing approach in an attempt to improve the quality. Concerning the product attributes, we found that there exist a significant difference of quality between open and close source projects, java and C projects, and large and small projects. Very small and defect free modules have impact on the software quality. Different complexity metrics have different impact on the software quality considering the size. Product complexity as defined in Table 53 has partial impact on the software quality. However software age and module dependencies are not factor to characterize the software quality. Concerning the people attributes, we found that platform experience, application experience and language and tool experience have significant impact on the software quality. Regarding the capability we found that programmer capability has partial impact on the software quality where as analyst capability has no impact on the software quality. Concerning process attributes we found that there is no difference of quality between the project developed under CMMI and those that are not developed under CMMI. Regarding the CMMI levels there is difference of software quality particularly between CMMI level 1 and CMMI level 3. Comparing different process types we found that hybrid projects are of better quality than waterfall projects. Process maturity defined by (SEI-CMM) has partial impact on the software quality. Concerning exploratory testing, we found that exploratory testing weaknesses induce the testing technical debt therefore a process is defined in conjunction with the scripted testing in an attempt to reduce the associated technical debt of exploratory testing. The findings are useful for both researchers and practitioners to evaluate their project