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Journal articles on the topic 'Software quality evaluation'

To see the other types of publications on this topic, follow the link: Software quality evaluation.

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Vaníček, J. "Software quality requirements." Agricultural Economics (Zemědělská ekonomika) 52, No. 4 (February 17, 2012): 177–85. http://dx.doi.org/10.17221/5014-agricecon.

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At the present time, the international standards and technical reports for system and software product quality are dispersed in several series of normative documents (ISO/IEC 9126, ISO/IEC 14598, ISO/IEC 12119 etc.). These documents are not purely consistent and do not contain a tools for exact requirements set-ups. As quality is defined as a degree to which the set of inherent characteristic fulfils requirements, the exact requirement formulation is the key point for the quality measurement evaluation. This paper presents the framework for quality requirements for software, which is recommendable to use in the new international standard series ISO/IEC 250xx developed on the SQuaRE (Software Quality Requirements and Evaluation) standardisation research project. The main part of this contribution was presented on the conference Agrarian Perspectives XIV, organised by the Czech University of Agriculture in Prague, September 20 to 21, 2005.

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2

Vaníček, J. "Software and data quality." Agricultural Economics (Zemědělská ekonomika) 52, No. 3 (February 17, 2012): 138–46. http://dx.doi.org/10.17221/5007-agricecon.

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The paper presents new ideas in the International SQuaRE (Software Quality Requirements and Evaluation) standardisation research project, which concerns the development of a special branch of international standards for software quality. Data can be considered as an integral part of software. The current international standard and technical report of the ISO/IEC 9126, ISO/IEC 14598 series and ISO/IEC 12119 standard covert the whole software as an indivisible entity. However, such data sets as databases and data stores have a special character and need a different structure of quality characteristic. Therefore it was decided in the SQuaRE project create a special international standard for data quality. The main idea for this standard and the critical discussion of these ideas is presented in this paper. The main part of this contribution was presented on the conference Agricultural Perspectives XIV, aligned by Czech University of Agriculture in Prague, September 20 to 21, 2005.

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3

Thompson, William E. "Software Quality Assurance and Evaluation." Journal of Quality Technology 23, no. 3 (July 1991): 264. http://dx.doi.org/10.1080/00224065.1991.11979334.

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4

Ajith Jubilson, E., and Ravi Sankar Sangam. "Software Metrics for Computing Quality of Software Agents." Journal of Computational and Theoretical Nanoscience 17, no. 5 (May 1, 2020): 2035–38. http://dx.doi.org/10.1166/jctn.2020.8845.

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Metrics are the essential building blocks for any evaluation process. They establish specific goals for improvement. Multi agent system (MAS) is complex in nature, due to the increase in complexity of developing a multi agent system, the existing metrics are less sufficient for evaluating the quality of an MAS. This is due to the fact that agent react in an unpredictable manner. Existing metrics for measuring MAS quality fails to addresses potential communication, initiative behaviour and learn-ability. In this work we have proposed additional metrics for measuring the software agent. A software agent for online shopping system is developed and the metrics values are obtained from it and the quality of the multi agent system is analysed.

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5

LAN, Yu-Qing, Tong ZHAO, Jing GAO, Hui JIE, and Mao-Zhong JIN. "Quality Evaluation of Foundational Software Platform." Journal of Software 20, no. 3 (March 9, 2010): 567–82. http://dx.doi.org/10.3724/sp.j.1001.2009.03443.

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6

McDaniel, James G. "Improving system quality through software evaluation." Computers in Biology and Medicine 32, no. 3 (May 2002): 127–40. http://dx.doi.org/10.1016/s0010-4825(02)00010-0.

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7

Bowen, John B. "Comments on software quality evaluation guidebook." ACM SIGSOFT Software Engineering Notes 11, no. 1 (January 1986): 19. http://dx.doi.org/10.1145/382300.382305.

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8

Kumar, Pradeep, Raghav Yadav, and Dileram Bansal. "Usability and Evaluation of Software Quality using Software Metrics." International Journal of Computer Applications 71, no. 3 (June 26, 2013): 9–14. http://dx.doi.org/10.5120/12336-8606.

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9

VILLALBA, M. TERESA, LUIS FERNÁNDEZ-SANZ, JUAN J. CUADRADO-GALLEGO, and JOSE J. MARTÍNEZ. "SOFTWARE QUALITY EVALUATION FOR SECURITY COTS PRODUCTS." International Journal of Software Engineering and Knowledge Engineering 20, no. 01 (February 2010): 27–48. http://dx.doi.org/10.1142/s0218194010004633.

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Increasing demand for security commercial products requires an improvement of methods for evaluating their software quality. Existing standards offer general frameworks but more specific models which reflect the perception of experts and customers as well as the particular characteristics of this type of products are needed. This article presents a method for generating domain-oriented software quality models for specific types of applications. It is applied to the generation of a model for security COTS products based on systematic review of standards, related literature and conclusions of evaluation experiences as well as the statistical analysis of information collected from 203 security experts and practitioners. Results reveal interesting conclusions on the importance given by users to the different quality characteristics of security commercial software products.

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10

Liu, Xiao Ying, and Jian Zhang. "Software Quality Evaluation for Vehicle Based on Set Pair Theory." Applied Mechanics and Materials 738-739 (March 2015): 1332–37. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.1332.

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A software quality evaluation method for vehicle based on set pair theory was proposed. The evaluating index system of software quality evaluation for vehicle was constructed. The software quality evaluation models were constructed by using four-element connection number of set pair theory. Then the computer-implemented method was given, and was verified by an example. Finally, the practical application showed that the evaluation method was simple, effective and had good practicality.

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11

Liu, Xiao Ying, and Jian Zhang. "Software Quality Evaluation for Control System Based on Extension Theory." Advanced Materials Research 945-949 (June 2014): 3331–35. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.3331.

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A software quality evaluation method for control system based on the extension engineering analysis method is proposed. The evaluating index system of software quality evaluation for control system was constructed. The matter elements models were constructed, and the goodness of mechanical design scheme was computed by using goodness evaluation method based on correlation function calculation. Then the pros or cons of system to be evaluated were determined by comparing the goodness value of each evaluation grade. Finally, the practical application showed that the evaluation method was scientific, clear, and effective and had good practicality.

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12

WASHIZAKI, Hironori, KOBAYASHI Yasuhide, WATANABE Hiroyuki, Eiji NAKAJIMA, Yuji HAGIWARA, Kenji HIRANABE, and Kazuya FUKUDA. "Quality Evaluation of Embedded Software in Robot Software Design Contest." Progress in Informatics, no. 4 (March 2007): 63. http://dx.doi.org/10.2201/niipi.2007.4.6.

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13

Kannabiran, Ganesan, and K. Sankaran. "Evaluation of Determinants of Software Quality in Offshored Software Projects." International Journal of Information Technology Project Management 11, no. 1 (January 2020): 32–54. http://dx.doi.org/10.4018/ijitpm.2020010103.

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Successful offshoring engagements of Indian software vendors is increasingly dependent upon the quality of the projects delivered rather than cost considerations. However, delivering quality software is reliant on effective management of various organizational, technological and people aspects. This research is to identify and evaluate the determinants of quality on software projects delivered by vendors through offshoring. Data related to recently completed projects were collected through a survey of 440 project managers from Indian vendors. Based on structural equation modeling, the authors analyze the influence determinants on specific product quality attributes. It is found that, out of six determinants, technical infrastructure and process maturity have significant influence on most of the attributes of quality in offshored IS projects from India. The authors provide a set of implications for practice and directions for further research.

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14

HAJDU-MACELARU, MARA, and IOANA ZELINA. "An adaptable software quality model." Creative Mathematics and Informatics 27, no. 1 (2018): 31–35. http://dx.doi.org/10.37193/cmi.2018.01.05.

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Just about everything changes, and so should a software quality model in order to provide a better understanding of quality for any software product to which is applied. But how can we develop such a software quality model? A software quality model pattern that can be adapted to different software products, and provide an accurate evaluation of the overall software quality. This paper presents an adaptable software quality model which is intended to be used for the quality evaluation of different software products.

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15

Park, Ju-Byung, and Hae-Sool Yang. "Quality Evaluation Method of Open Source Software." Journal of the Korea Academia-Industrial cooperation Society 13, no. 5 (May 31, 2012): 2353–59. http://dx.doi.org/10.5762/kais.2012.13.5.2353.

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16

Wenying Zhang, Suqin Feng, Jinyu Guan, and Yongchun Xu. "A Synthetic Evaluation Method for Software Quality." Journal of Convergence Information Technology 8, no. 9 (May 15, 2013): 506–12. http://dx.doi.org/10.4156/jcit.vol8.issue9.63.

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17

Kumar, Renu, Suresh Rai, and L. Trahan Jerry. "Neural-network techniques for software-quality evaluation." Computer Standards & Interfaces 21, no. 2 (June 1999): 158. http://dx.doi.org/10.1016/s0920-5489(99)92147-5.

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18

Kalmar, Ralf, Thorsten Keuler, Jens Knodel, and Matthias Naab. "Effective Quality Assurance with Software Architecture Evaluation." ATZelektronik worldwide 6, no. 5 (October 2011): 22–25. http://dx.doi.org/10.1365/s38314-011-0048-z.

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19

Kopyltsov, A. V. "Selection of metrics in software quality evaluation." Journal of Physics: Conference Series 1515 (April 2020): 032018. http://dx.doi.org/10.1088/1742-6596/1515/3/032018.

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20

Maroto, Concepion, and Pilar Tormos. "Project Management: an Evaluation of Software Quality." International Transactions in Operational Research 1, no. 2 (April 1994): 209–21. http://dx.doi.org/10.1111/1475-3995.d01-22.

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21

Xiao-ying, Shi, and Yang Lan. "A software quality evaluation system: JT-SQE." Wuhan University Journal of Natural Sciences 6, no. 1-2 (March 2001): 511–15. http://dx.doi.org/10.1007/bf03160294.

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22

Maroto, C. "Project management: an evaluation of software quality." International Transactions in Operational Research 1, no. 2 (April 1994): 209–21. http://dx.doi.org/10.1016/0969-6016(94)90021-3.

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23

Chopra, Kunal, and Monika Sachdeva. "EVALUATION OF SOFTWARE METRICS FOR SOFTWARE PROJECTS." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 14, no. 6 (April 30, 2015): 5845–53. http://dx.doi.org/10.24297/ijct.v14i6.1915.

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Software metrics are developed and used by the many software organizations for the evaluation and confirmation of good code, working and maintenance of the software product. Software metrics measure and identify various types of software complexities such as size metrics, control flow metrics and data flow metrics. One of the significant objective of software metrics is that it is applicable to both a process and product metrics. Ndepend is the most advanced as well as flexible tool available in the market. We have ensured the Quality of the project by using Ndepend metrics. So we have concluded that software metrics are easy to understand and applicable on the software, so favourable among software professionals.It is most prevalent and important testing metrics used in organizations. Metrics are used to improve software productivity and quality. This thesis introduces the most commonly used software metrics proposed and reviews their use in constructing models of the software development process.

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24

Yuan, Xiao Tong, and Hua Min Yang. "The Software Quality Fuzzy Comprehensive Evaluation Method Research." Applied Mechanics and Materials 513-517 (February 2014): 1959–62. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1959.

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For the data is fuzziness and the uncertainty on software quality evaluation,on the basis of ISO 9126 quality model,an evaluation model of software quality is established based on fuzzy comprehensive evaluation and analytic hierarchy process in this paper.Through the establishment of software quality evaluation model, we can solve the multi-index evaluation problems of software quality effectively and it can be used to guide users to improve software process.

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25

Denham, Benjamin, Russel Pears, and Andy M. Connor. "Evaluating the Quality of Drupal Software Modules." International Journal of Software Engineering and Knowledge Engineering 28, no. 05 (May 2018): 663–700. http://dx.doi.org/10.1142/s0218194018500195.

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Evaluating software modules for inclusion in a Drupal website is a crucial and complex task that currently requires manual assessment of a number of module facets. This study applied data-mining techniques to identify quality-related metrics associated with highly popular and unpopular Drupal modules. The data-mining approach produced a set of important metrics and thresholds that highlight a strong relationship between the overall perceived reliability of a module and its popularity. Areas for future research into open-source software quality are presented, including a proposed module evaluation tool to aid developers in selecting high-quality modules.

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26

Chen, Jiqiang, Litao Ma, Chao Wang, Hong Zhang, and Jie Wan. "A New Uncertainty Evaluation Method and Its Application in Evaluating Software Quality." Journal of Applied Mathematics 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/145285.

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Uncertainty theory is a branch of axiomatic mathematics dealing with experts’ belief degree. Considering the uncertainty with experts’ belief degree in the evaluation system and the different roles which different indices play in evaluating the overall goal with a hierarchical structure, a new comprehensive evaluation method is constructed based on uncertainty theory. First, index scores and weights of indices are described by uncertain variables and evaluation grades are described by uncertain sets. Second, weights of indices with respect to the overall goal are introduced. Third, a new uncertainty comprehensive evaluation method is constructed and proved to be a generalization of the weighted average method. Finally, an application is developed in evaluating software quality, which shows the effectiveness of the new method.

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27

Hrytsiuk, Yu I., and O. R. Ferneza. "Reflection of expert-based evaluation of software quality." Scientific Bulletin of UNFU 29, no. 8 (October 31, 2019): 152–58. http://dx.doi.org/10.36930/40290828.

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The method of reflections data, which is obtained as a result of processing expert-based evaluation of software quality by different criteria of evaluation using petal charts. Reflection of expert-based evaluation of software quality is found to be the process of reflections data in graphical form for maximum ease of understanding and rapid perception, and also providing a clear overview and shape of any object, process or phenomenon. The software quality evaluation criteria and their weighting factors for each expert are offered, which provide a reliable presentation of the current state of the software development process, a proper understanding of the problems that may arise at any stage of the program project implementation, and the exact characteristics of their components. This mechanism of data reflection enables business analysts to submit qualitatively and quantitatively multiple values of complex software quality indicators that can be obtained from the results of any survey of different experts at a particular stage of the program project implementation. The proposed methodology is suitable for presenting a variety of expert survey results, with a subdivision into unlimited number of the roles of the software quality evaluation participants concerning the importance of each of them. An algorithm for calculating the area of sectorial petals in a polar coordinate system has been developed, using which it is possible to calculate and evaluate the relative software quality according to the proper criteria. The final complex software quality indicators for each expert are determined, and a comprehensive indicator of its quality is summarized as well. An algorithm for calculating the area of a petal diagram in a polar coordinate system has been developed, which allows determining the part of software quality according to all the criteria, which is currently evaluated by one of the experts, as well as the part of software quality, which has yet to be achieved for its 100% completeness. The relevant conclusions are drawn and recommendations are made concerning the use of the developed data reflection methodology.

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28

Chung, Su-min, Jae-hyun Choi, and Jea-won Park. "Design of Software Quality Evaluation Model for IoT." Journal of the Korea Institute of Information and Communication Engineering 20, no. 7 (July 31, 2016): 1342–54. http://dx.doi.org/10.6109/jkiice.2016.20.7.1342.

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29

Pasrija, Vatesh, and Praveen Ranjan Srivastava. "Evaluation of Software Quality using Choquet Integral Approach." International Journal of Fuzzy System Applications 3, no. 1 (January 2013): 51–81. http://dx.doi.org/10.4018/ijfsa.2013010104.

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Software development comprises of processes which can be controlled, managed and improved by software measurement. The efficiency of software measurement is determined by software quality, which assesses the position of any software company in the international economic scenario. This calls for a need to develop quality models which would quantify the various quality parameters. However, these quality parameters are highly vague, by nature, and cannot be easily quantized nor measured. The Boehm’s Model, McCall’s Model, and ISO/IEC 9126 Model are existing quality models made by software quality researchers in this regard. This paper uses the ISO/IEC 9126 quality model as the baseline model, with enhanced criteria, to give a holistic approach to software quality. A methodology is proposed in this paper for comparing different software solutions based on the SRS to a common problem. As software product quality is highly unpredictable, and considering the interaction between the quality criteria, Choquet Integral is used to efficiently compare the set of software products.

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30

M. Alashqar, Abdelkareem, Ahmad Abo Elfetouh, and Hazem M. El-Bakry. "ISO9126 Based Software Quality Evaluation Using Choquet Integral." International Journal of Software Engineering & Applications 6, no. 1 (January 31, 2015): 111–21. http://dx.doi.org/10.5121/ijsea.2015.6110.

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31

Bukovsky, Nikolay S. "Building an expert system for software quality evaluation." Microprocessing and Microprogramming 28, no. 1-5 (March 1990): 179–82. http://dx.doi.org/10.1016/0165-6074(90)90170-e.

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32

Takahashi, Ryouei, and Yoichi Muraoka. "Building software quality classification trees: Approach, experimentation, evaluation." Computer Standards & Interfaces 21, no. 2 (June 1999): 168–69. http://dx.doi.org/10.1016/s0920-5489(99)92188-8.

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33

WOJCIECHOWSKI, Zdzisław. "Analysis and evaluation of software quality in use." PROBLEMY JAKOŚCI 1, no. 9 (September 5, 2018): 132–37. http://dx.doi.org/10.15199/48.2018.9.18.

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34

Cho, Sang-Young, and Sung-Kyu Yoo. "A Quality Evaluation Model for Hardware-Control Software." Advanced Science Letters 23, no. 10 (October 1, 2017): 9607–11. http://dx.doi.org/10.1166/asl.2017.9757.

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35

Zhao, Yi-Ding, Zhi-Min Li, and Xi-Guang Zhang. "Model for Software Quality Evaluation with Fuzzy Information." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 7394–98. http://dx.doi.org/10.1166/jctn.2016.5732.

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To study the problem of multiple attribute decision making in which the decision making information values are triangular fuzzy number, a relative entropy decision making method for software quality evaluation is proposed. Then, according to the concept of the relative entropy, the relative closeness degree is defined to determine the ranking order of all alternatives by calculating the relative entropy to both the fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) simultaneously. At last, a numerical example for software quality evaluation is provided to illustrate the proposed method. The result shows the approach is simple, effective and easy to calculate.

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36

Han, WanJiang, WeiJian Li, HeYang Jiang, TianBo Lu, and Xiaoyan Zhang. "Software Project Quality Evaluation Model for Web Application." International Journal of Multimedia and Ubiquitous Engineering 10, no. 5 (May 31, 2015): 111–22. http://dx.doi.org/10.14257/ijmue.2015.10.5.12.

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37

Davydenko, George, Victor Gurvich, and Mark Smekhov. "Application of StatPhantom Software for Image Quality Evaluation." Journal of Digital Imaging 15 (April 1, 2002): 219–20. http://dx.doi.org/10.1007/s10278-002-5013-1.

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38

P. Miguel, José, David Mauricio, and Glen Rodríguez. "A Review of Software Quality Models for the Evaluation of Software Products." International Journal of Software Engineering & Applications 5, no. 6 (November 30, 2014): 31–53. http://dx.doi.org/10.5121/ijsea.2014.5603.

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39

Zhuang, Ting, and Yan Yan Zuo. "Research on Subjective and Objective Evaluation of Car Interior Sound Quality." Applied Mechanics and Materials 455 (November 2013): 193–97. http://dx.doi.org/10.4028/www.scientific.net/amm.455.193.

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This experiment collected sound signals of four different cars driving at different speeds on highway and replayed the noise samples with playback software HEAD Audio Recorder. The subjective evaluation tests were carried out with paired comparison method. Evaluating models between subjective evaluation and objective psychoacoustic parameters were established with SPSS analysis software.

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40

Efstathopoulos, E. P., O. Benekos, M. Molfetas, E. Charou, S. Kottou, S. Argentos, and N. L. Kelekis. "Quality assurance (QA) procedures for software: evaluation of an ADC quality system." Radiation Protection Dosimetry 117, no. 1-3 (December 1, 2005): 291–97. http://dx.doi.org/10.1093/rpd/nci742.

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41

Welzel, Dieter, Hans-Ludwig Hausen, and Jøsrgen Bøsegh. "A metric-based software evaluation method." Software Testing, Verification and Reliability 3, no. 3-4 (September 1993): 181–94. http://dx.doi.org/10.1002/stvr.4370030306.

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42

Challa, Jagat Sesh, Arindam Paul, Yogesh Dada, Venkatesh Nerella, Praveen Ranjan Srivastava, and Ajit Pratap Singh. "Integrated Software Quality Evaluation: A Fuzzy Multi-Criteria Approach." Journal of Information Processing Systems 7, no. 3 (September 30, 2011): 473–518. http://dx.doi.org/10.3745/jips.2011.7.3.473.

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43

Banerjee, Prasenjit, and Anirban Sarkar. "Quality Evaluation of Component-Based Software: An Empirical Approach." International Journal of Intelligent Systems and Applications 10, no. 12 (December 8, 2018): 80–91. http://dx.doi.org/10.5815/ijisa.2018.12.08.

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44

Kara, Madjid, Olfa Lamouchi, and Amar Ramdane-Cherif. "Ontology Software Quality Model for Fuzzy Logic Evaluation Approach." Procedia Computer Science 83 (2016): 637–41. http://dx.doi.org/10.1016/j.procs.2016.04.143.

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45

Entringer, Tulio Cremonini, and Ailton Da Silva Ferreira. "Software quality evaluation: a bibliometric analysis and future perspectives." Independent Journal of Management & Production 10, no. 5 (October 1, 2019): 1499. http://dx.doi.org/10.14807/ijmp.v10i5.911.

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The theme of “Software Quality Evaluation”, and its importance, concerns the standardization of the development processes, in order to guarantee a higher quality of the systems. In this scenario, this theme has gained importance in academic research, due to the emphasis that the theme has increasingly presented to organizations, since they understand that the main objective is to guarantee a final product that satisfies the expectations of the client. In order to verify the scientific scenario in recent years, this work aims to carry out a review of the literature on “Software Quality Evaluation”, based on a bibliometric analysis and review. For this, the method of bibliographic revision with four different phases proposed by Marasco (2008) was used. From the data extracted from the Scopus database, the results of the systematic review and bibliometric analysis were analyzed from the information on publications, citations and approaches of the papers that deal with this subject. As results, the present article showed the academic and practical importance of the studies on “Software Quality Evaluation”. In addition, it is possible to identify gaps in the scientific literature that can be filled by future work in the area, based on the studies developed by specialists.

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46

Lee, Jung-Hyun, Jae-Hyun Choi, and Jea-Won Park. "A Practical Quality Evaluation Model of Mobile Cloud Software." Journal of Korean Institute of Information Technology 13, no. 3 (March 31, 2015): 95. http://dx.doi.org/10.14801/jkiit.2015.13.3.95.

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47

Boegh, J., S. Depanfilis, B. Kitchenham, and A. Pasquini. "A method for software quality planning, control, and evaluation." IEEE Software 16, no. 2 (1999): 69–77. http://dx.doi.org/10.1109/52.754056.

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48

Yang, D., J. Tan, L. Appenzoller, H. Li, B. Sun, and S. Mutic. "A Computer Software Tool for Comprehensive Plan Quality Evaluation." International Journal of Radiation Oncology*Biology*Physics 87, no. 2 (October 2013): S620. http://dx.doi.org/10.1016/j.ijrobp.2013.06.1640.

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49

Kim, Hyo-Yeong, Han-Han Kim, Hyeok-Su Han, Sun-Yong Kim, Seok-Gyu Sin, and Yeong-Eun Jeong. "A study on the evaluation of package software documentation to improve software quality." KIPS Transactions:PartD 9D, no. 4 (August 1, 2002): 629–38. http://dx.doi.org/10.3745/kipstd.2002.9d.4.629.

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50

Kehinde, Moses. "Evaluation of Quantitative Process and Software Quality Management in the Nigerian Software-House." International Journal of Computer Applications 168, no. 1 (June 15, 2017): 29–36. http://dx.doi.org/10.5120/ijca2017914273.

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