Quality Properties of Execution Tracing, an Empirical Study

The authors are grateful to all the professionals who participated in the focus groups; moreover, they also express special thanks to the management of the companies involved for making the organisation of the focus groups possible.Data are made available in the appendix including the results of the data coding process.The quality of execution tracing impacts the time to a great extent to locate errors in software components; moreover, execution tracing is the most suitable tool, in the majority of the cases, for doing postmortem analysis of failures in the field. Nevertheless, software product quality models do not adequately consider execution tracing quality at present neither do they define the quality properties of this important entity in an acceptable manner. Defining these quality properties would be the first step towards creating a quality model for execution tracing. The current research fills this gap by identifying and defining the variables, i.e., the quality properties, on the basis of which the quality of execution tracing can be judged. The present study analyses the experiences of software professionals in focus groups at multinational companies, and also scrutinises the literature to elicit the mentioned quality properties. Moreover, the present study also contributes to knowledge with the combination of methods while computing the saturation point for determining the number of the necessary focus groups. Furthermore, to pay special attention to validity, in addition to the the indicators of qualitative research: credibility, transferability, dependability, and confirmability, the authors also considered content, construct, internal and external validity

Practical Consequences of Quality Views in Assessing Software Quality

open access articleThe authors’ previously published research delved into the theory of software product quality modelling, model views, concepts, and terminologies. They also analysed this specific field from the point of view of uncertainty, and possible descriptions based on fuzzy set theory and fuzzy logic. Laying a theoretical foundation was necessary; however, software professionals need a more tangible and practical approach for their everyday work. Consequently, the authors devote this paper to filling in this gap; it aims to illustrate how to interpret and utilise the previous findings, including the established taxonomy of the software product quality models. The developed fuzzy model’s simplification is also presented with a Generalized Additive Model approximation. The paper does not require any formal knowledge of uncertainty computations and reasoning under uncertainty, nor does it need a deep understanding of quality modelling in terms of terminology, concepts, and meta-models, which were necessary to prepare the taxonomy and relevance ranking. The paper investigates how to determine the validity of statements based on a given software product quality model; moreover, it considers how to tailor and adjust quality models to the particular project’s needs. The paper also describes how to apply different software product quality models for different quality views to take advantage of the automation potential offered for the measurement and assessment of source code quality. Furthermore, frequent pitfalls are illustrated with their corresponding resolutions, including an unmeasured quality property that is found to be important and needs to be included in the measurement and assessment process

Software Product Quality Models, Developments, Trends and Evaluation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Software product quality models have evolved in their abilities to capture and describe the abstract notion of software quality since the 1970’s. Many models constructed deal with a specific part of software quality only which makes them ineligible to assess the quality of software products as a whole. Former publications failed to thoroughly examine and list all the available models which attempt to describe each known property of software product quality. This paper discovers such complete software product quality models published since 2000; moreover, it endeavours to measure the relevance of each model quantitatively by introducing indicators with regard to the scientific and industrial community. The identified 23 software product quality model classes differ significantly in terms of publication intensity, publication range, quality score average, relevance score and the 12-month average of the Google Relative Search Index. The results offer a foundation for selecting the appropriate software product quality model for use or for extension if newly identified quality properties need to be connected to a general context. Furthermore, the experiences accumulated on the field of software product quality modelling motivated researchers to successfully transfer the concepts to other areas where abstract entities need to be compared or assessed including the quality of higher educational teaching and business processes, which is also briefly highlighted in the paper

Fuzzy Logic Based Software Product Quality Model for Execution Tracing

This report presents the research carried out in the area of software product quality modelling. Its main endeavour is to consider software product quality with regard to maintainability. Supporting this aim, execution tracing quality, which is a neglected property of the software product quality at present in the quality frameworks under investigation, needs to be described by a model that offers possibilities to link to the overall software product quality frameworks. The report includes concise description of the research objectives: (1) the thorough investigation of software product quality frameworks from the point of view of the quality property analysability with regard to execution tracing; (2) moreover, extension possibilities of software product quality frameworks, and (3) a pilot quality model developed for execution tracing quality, which is capable to capture subjective uncertainty associated with the software quality measurement. The report closes with concluding remarks: (1) the present software quality frameworks do not exhibit any property to describe execution tracing quality, (2) execution tracing has a significant impact on the analysability of software systems that increases with the complexity, and (3) the uncertainty associated with execution tracing quality can adequately be expressed by type-1 fuzzy logic. The section potential future work outlines directions into which the research could be continued. Findings of the research were summarized in two research reports, which were also incorporated in the thesis, and submitted for publication: 1. Tamas Galli, Francisco Chiclana, Jenny Carter, Helge Janicke, “Towards Introducing Execution Tracing to Software Product Quality Frameworks,” Acta Polytechnica Hungarica, vol. 11, no. 3, pp. 5-24, 2014. doi: 10.12700/APH.11.03.2014.03.1 2. Tamas Galli, Francisco Chiclana, Jenny Carter, Helge Janicke “Modelling Execution Tracing Quality by Means of Type-1 Fuzzy Logic,” Acta Polytechnica Hungarica, vol. 10, no. 8, pp. 49-67, 2013. doi: 10.12700/APH.10.08.2013.8.

Data Science Techniques for Modelling Execution Tracing Quality

This research presents how to handle a research problem when the research variables are still unknown, and no quantitative study is possible; how to identify the research variables, to be able to perform a quantitative research, how to collect data by means of the research variables identified, and how to carry out modelling with the considerations of the specificities of the problem domain. In addition, validation is also encompassed in the scope of modelling in the current study. Thus, the work presented in this thesis comprises the typical stages a complex data science problem requires, including qualitative and quantitative research, data collection, modelling of vagueness and uncertainty, and the leverage of artificial intelligence to gain such insights, which are impossible with traditional methods. The problem domain of the research conducted encompasses software product quality modelling, and assessment, with particular focus on execution tracing quality. The terms execution tracing quality and logging are used interchangeably throughout the thesis. The research methods and mathematical tools used allow considering uncertainty and vagueness inherently associated with the quality measurement and assessment process through which reality can be approximated more appropriately in comparison to plain statistical modelling techniques. Furthermore, the modelling approach offers direct insights into the problem domain by the application of linguistic rules, which is an additional advantage. The thesis reports (1) an in-depth investigation of all the identified software product quality models, (2) a unified summary of the identified software product quality models with their terminologies and concepts, (3) the identification of the variables influencing execution tracing quality, (4) the quality model constructed to describe execution tracing quality, and (5) the link of the constructed quality model to the quality model of the ISO/IEC 25010 standard, with the possibility of tailoring to specific project needs. Further work, outside the frames of this PhD thesis, would also be useful as presented in the study: (1) to define application-project profiles to assist tailoring the quality model for execution tracing to specific application and project domains, and (2) to approximate the present quality model for execution tracing, within defined bounds, by simpler mathematical approaches. In conclusion, the research contributes to (1) supporting the daily work of software professionals, who need to analyse execution traces; (2) raising awareness that execution tracing quality has a huge impact on software development, software maintenance and on the professionals involved in the different stages of the software development life-cycle; (3) providing a framework in which the present endeavours for log improvements can be placed, and (4) suggesting an extension of the ISO/IEC 25010 standard by linking the constructed quality model to that. In addition, in the scope of the qualitative research methodology, the current PhD thesis contributes to the knowledge of research methods with determining a saturation point in the course of the data collection process