scholarly journals Copula-based software metrics aggregation

Author(s):  
Maria Ulan ◽  
Welf Löwe ◽  
Morgan Ericsson ◽  
Anna Wingkvist

AbstractA quality model is a conceptual decomposition of an abstract notion of quality into relevant, possibly conflicting characteristics and further into measurable metrics. For quality assessment and decision making, metrics values are aggregated to characteristics and ultimately to quality scores. Aggregation has often been problematic as quality models do not provide the semantics of aggregation. This makes it hard to formally reason about metrics, characteristics, and quality. We argue that aggregation needs to be interpretable and mathematically well defined in order to assess, to compare, and to improve quality. To address this challenge, we propose a probabilistic approach to aggregation and define quality scores based on joint distributions of absolute metrics values. To evaluate the proposed approach and its implementation under realistic conditions, we conduct empirical studies on bug prediction of ca. 5000 software classes, maintainability of ca. 15000 open-source software systems, and on the information quality of ca. 100000 real-world technical documents. We found that our approach is feasible, accurate, and scalable in performance.

2019 ◽  
Vol 3 (2) ◽  
pp. 74
Author(s):  
Mazen Ismaeel Ghareb ◽  
Garry Allen

   The quality evaluation of software metrics measurement is considered as the primary indicator of imperfection prediction and software maintenance in various empirical studies of software products. However, there is no agreement on which metrics are compelling quality pointers for new software development approaches such as aspect-oriented programming (AOP) techniques. AOP intends to enhance programming quality by providing fundamentally different parts of the systems, for example, pointcuts, advice, and intertype relationships. Hence, it is not evident if quality characteristics for AOP could be extracted from direct expansions of traditional object-oriented programming (OOP) measurements. Then again, investigations of AOP do regularly depend on established static and dynamic metrics measurement; notwithstanding the late research of AOP in empirical studies, few analyses been adopted using the International Organization for Standardization 9126 quality model as useful markers of flaw inclination in this context. This paper examination we have considered different programming quality models given by various authors every once in a while and distinguished that adaptability was deficient in the current model. We have testing 10 projects developed by AOP. We have used many applications to extract the metrics, but none of them could extract all AOP Metrics. It only can measure some of AOP Metrics, not all of them. This study investigates the suitable framework for extract AOP Metrics, for instance, static and dynamic metrics measurement for hybrid application systems (AOP and OOP) or only AOP application.


2014 ◽  
Author(s):  
Mariana Santos ◽  
Rodrigo Amador ◽  
Paulo Henrique De Souza Bermejo ◽  
Heitor Costa

Organizations are becoming increasingly concerned about software quality. In object-oriented (OO) systems, quality is characterized by measurements of internal quality attributes. An efficient and proper method to analyze software quality in the absence of fault-prone or defective data labels is cluster analysis. The aim of this paper is to find similarities among project structures by measuring characteristics of internal software quality. In a sample of 150 open-source software systems, we evaluated software using macro and micro categories. Results obtained using cluster analysis indicated that some domains such as Graphics, Games, and Development tend to have similarities in specialization, abstraction, stability, and complexity. These results exploit the ability of OO software metrics to find similar behavior across domains. The results provide an immediate view of the trends and characteristics of internal software quality of Java systems that need to be addressed so that software systems can continue to be maintainable.


2013 ◽  
Vol 63 (1) ◽  
Author(s):  
Nor Fazlina Iryani Abdul Hamid ◽  
Mohamad Khatim Hasan

Software metric and quality models play a pivotal role in measurement of software quality. A number of well-known quality models and software metrics are used to build quality software in industry. Most developers and majority of software users require some form of measure for the software system they are concerned with. Software quality measurement needs a quality model that is usable throughout the software lifecycle and that it embraces all the perspectives of quality. Software quality factors and attributes that form the quality model is derived from literature review and survey. Using those quality factors and attributes, software quality model for telecommunication industry is constructed by considering three distinctive but connected areas of interest, which are economic dimension, social dimension and technical dimension. 


Author(s):  
Feidu Akmel ◽  
Ermiyas Birihanu ◽  
Bahir Siraj

Software systems are any software product or applications that support business domains such as Manufacturing,Aviation, Health care, insurance and so on.Software quality is a means of measuring how software is designed and how well the software conforms to that design. Some of the variables that we are looking for software quality are Correctness, Product quality, Scalability, Completeness and Absence of bugs, However the quality standard that was used from one organization is different from other for this reason it is better to apply the software metrics to measure the quality of software. Attributes that we gathered from source code through software metrics can be an input for software defect predictor. Software defect are an error that are introduced by software developer and stakeholders. Finally, in this study we discovered the application of machine learning on software defect that we gathered from the previous research works.


1989 ◽  
Vol 21 (8-9) ◽  
pp. 1015-1024 ◽  
Author(s):  
C. P. Crockett ◽  
R. W. Crabtree ◽  
I. D. Cluckie

In England and Wales the placing of effluent discharge consents within a statistical framework has led to the development of a new hybrid type of river quality model. Such catchment scale consent models have a stochastic component for the generation of model inputs and a deterministic component to route them through the river system. This paper reviews and compares the existing approaches for consent modelling used by various Water Authorities. A number of possible future developments are suggested including the potential need for a national approach to the review and setting of long term consents.


2021 ◽  
Vol 11 (12) ◽  
pp. 5690
Author(s):  
Mamdouh Alenezi

The evolution of software is necessary for the success of software systems. Studying the evolution of software and understanding it is a vocal topic of study in software engineering. One of the primary concepts of software evolution is that the internal quality of a software system declines when it evolves. In this paper, the method of evolution of the internal quality of object-oriented open-source software systems has been examined by applying a software metric approach. More specifically, we analyze how software systems evolve over versions regarding size and the relationship between size and different internal quality metrics. The results and observations of this research include: (i) there is a significant difference between different systems concerning the LOC variable (ii) there is a significant correlation between all pairwise comparisons of internal quality metrics, and (iii) the effect of complexity and inheritance on the LOC was positive and significant, while the effect of Coupling and Cohesion was not significant.


Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 88
Author(s):  
Xiamei Man ◽  
Chengwang Lei ◽  
Cayelan C. Carey ◽  
John C. Little

Many researchers use one-dimensional (1-D) and three-dimensional (3-D) coupled hydrodynamic and water-quality models to simulate water quality dynamics, but direct comparison of their relative performance is rare. Such comparisons may quantify their relative advantages, which can inform best practices. In this study, we compare two 1-year simulations in a shallow, eutrophic, managed reservoir using a community-developed 1-D model and a 3-D model coupled with the same water-quality model library based on multiple evaluation criteria. In addition, a verified bubble plume model is coupled with the 1-D and 3-D models to simulate the water temperature in four epilimnion mixing periods to further quantify the relative performance of the 1-D and 3-D models. Based on the present investigation, adopting a 1-D water-quality model to calibrate a 3-D model is time-efficient and can produce reasonable results; 3-D models are recommended for simulating thermal stratification and management interventions, whereas 1-D models may be more appropriate for simpler model setups, especially if field data needed for 3-D modeling are lacking.


Author(s):  
Julien Siebert ◽  
Lisa Joeckel ◽  
Jens Heidrich ◽  
Adam Trendowicz ◽  
Koji Nakamichi ◽  
...  

AbstractNowadays, systems containing components based on machine learning (ML) methods are becoming more widespread. In order to ensure the intended behavior of a software system, there are standards that define necessary qualities of the system and its components (such as ISO/IEC 25010). Due to the different nature of ML, we have to re-interpret existing qualities for ML systems or add new ones (such as trustworthiness). We have to be very precise about which quality property is relevant for which entity of interest (such as completeness of training data or correctness of trained model), and how to objectively evaluate adherence to quality requirements. In this article, we present how to systematically construct quality models for ML systems based on an industrial use case. This quality model enables practitioners to specify and assess qualities for ML systems objectively. In addition to the overall construction process described, the main outcomes include a meta-model for specifying quality models for ML systems, reference elements regarding relevant views, entities, quality properties, and measures for ML systems based on existing research, an example instantiation of a quality model for a concrete industrial use case, and lessons learned from applying the construction process. We found that it is crucial to follow a systematic process in order to come up with measurable quality properties that can be evaluated in practice. In the future, we want to learn how the term quality differs between different types of ML systems and come up with reference quality models for evaluating qualities of ML systems.


2021 ◽  
Vol 23 (1) ◽  
pp. 34-41
Author(s):  
Alejandro Vera-Baquero ◽  
Owen Phelan ◽  
Pawel Slowinski ◽  
John Hannon

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