Journal of Communication and Computer 9 (2012) 251-254
The Comprehensive Evaluation of Software Quality Bad on Fuzzy Theory
Guomin Liu1, Yu Song 1, Qingjie Zhou2 and Guoji Qu2
1. North China Electric Power University, Bao Ding City He Bei Province, 071003, China
2. Beijing join bright digital power technology Co. Ltd, Beijing, 100096, China
Received: November 29, 2011 / Accepted: December 01, 2011 / Published: March 31, 2012.
Abstract: It is in order to effectively identify and evaluate the quality of software development. We can develop the quality characteristics of software to analyze and summarize characteristics of the fuzzy comprehensive evaluation model level and get to do fuzzy evaluation matrix and its treatment. This paper us multi-level comprehensive evaluation method bad on fuzzy theory. Multi-level fuzzy comprehensive evaluation is ud to draw maximum degree of membership to discuss the issue, so as to software quality control and evaluation of a scientific basis.
Key words: Software development, software quality, fuzzy theory, comprehensive evaluation.
1 Introduction
Software quality has been troubled by software developers and managers of the main problems. Software quality [1-3] asssment not only for software quality control and assurance to provide reliable support, but also for the software tting, inspection, identification, evaluation and marketing provide an objective and scientific basis. Thus, software quality assurance software engineering is still the current rearch and explores the difficult and hot issues.
2. Software Quality and Software Metrics
2.1 Software Quality
Accordance with international standards, the definition of software quality[4-5]: software quality software products to meet with the explicit or implicit demand characteristics related to the ability and characteristics of the sum. Software quality and excellence in computer software that describe the
Yu Song, professor, rearch field: Software Engineering. Corresponding author: Guomin Liu, graduate student, rearch fields:, databa and information system. E-mail: *************.characteristics are cloly related.
2.2 Software Metrics
Measure is the number or symbol assigned to the object or event, although the nature of this assignment is empirical, but the assigned value or symbol must be measured to reflect the properties of things: a measure of any of the following four elements must be included: (1) the entity to be measured; (2) the properties of the entity to be measured; (3) values or symbols of the given entity.
3. Multi-Level Software Quality Evaluation Index Systems
Software quality factors [6-7] vary with different applications. It can be as demand changes, it is a complex mixture which is not fixed. Therefore, for different situations and different situations, it will form a different software quality factors, including McCall, Richards.
3.1 Index System Design Principles
In the evaluation of software quality, the first need to
establish the evaluation index system, and then u the
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肥皂的制作The Comprehensive Evaluation of Software Quality Bad on Fuzzy Theory 252
appropriate method of evaluation. Establishment of indicators to be considered when the following principles: the principle of scientific, systematic principle, the principle of comparability, quantitative indicators and qualitative indicators to asss the principle of combining practical principles.
3.2 Multi-level Indicators to Establish
Currently, the software quality evaluation index system of rearch has matured and reached a connsus, which raid more influential is the factors and software quality measurement system Propod by McCall. He believes that the factors that influence software quality are divided into two categories: one can directly measure factors such as errors per function point; the cond is only an indirect measure of factors. Both cas should be able to measure software technology, through the software documentation, procedures, data to do some more, can be measured in a variety of software technology affect the quality factor judge value.
人力资源发展规划
Bad on the above principles and related knowledge to build a software quality evaluation index system as shown in Table 1. One small table in brackets is the corresponding weight factors, the so-called weight, which refers to the weight of an index is the index in the overall evaluation of the relative importance.
4.Bad on the Theory of Fuzzy Comprehensive Evaluation of Software Quality
六爻卦4.1 The First-level Model
A○R = B = (b1, b2, b3, b4) (1)
R = (r ij) n×m, r ij∈[0,1] (2)
(3) Where A is the weight, R is the evaluation matrix, B the evaluation results, this model us the real number addition and subtraction, more sophisticated operations than using “∨”and “∧”.
4.2 Multi-level Model劝学荀子
In the single-stage on the basis of the formula, we then factor into a number of components. Then be a model operation, respectively. Then be combined to find the new R, then you can follow a single-stage
sub-factors and a judge of the results, and C is the last comprehensive evaluation of the results. When the calculated normalized C (C1, C2, C3, C4), the principle of maximum membership obtained by the results of safety evaluation.
In this paper, fuzzy evaluation method to improve and add restrictions. Becau both the level or multi-level model creation process, we are to each factor as an independent entity to conduct the calculations, so we will ignore a problem that when a value is too low under the factors , it will affect the entire system of evaluation, or even wrong judge. So in this article by adding the value of each factor under the conditions of the minimum can be judged more scientific results.
4.3 Pairs a Comprehensive Evaluation of Software Quality
We assume that the condition that the minimum weight limit of 0.12. Since each element given in Table 1 is greater than the weight restrictions, the fuzzy comprehensive evaluation algorithm is deter
mined using Table 1 to establish a software product quality evaluation index system of evaluation can be implemented. Clearly, the quality asssment of software products are multi-level fuzzy comprehensive evaluation, the specific implementation steps are as follows:
n n
b j= ∑ a i r ij j=1,....,m ∑b i=1
i=1i=1
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The Comprehensive Evaluation of Software Quality Bad on Fuzzy Theory
253
Table 1 Index system and weight of software quality. Asssment of the object
潮湿的季节Level indicators (Weight)
Two indicators (Weight)
Three indicators
(Weight) Evaluation results Excellent Good General bad Software Product
Quality
Product revision (0.45)
Maintainability (1
/ 3)
Simplicity (1/5) 0.75 0.15 0.1 0
Consistency (1/5) 0.85 0.15 0 0 Auto review (1/5) 0.87 0.1 0.03 0
Modularity (1/5) 0.92 0.08 0 0 Security (1/5) 0.86 0.1 0.04 0 Flexibility (1/3) Complexity (1/7) 0.84 0.12 0.04 0 Simplicity (1/7) 0.79 0.11 0.1 0 Consistency (1/7) 0.92 0.08 0 0 Scalability (1/7) 0.90 0.08 0.02 0 Versatility (1/7) 0.87 0.13 0 0 Modularity (1/7) 0.86 0.09 0.06 0 Security (1/7) 0.95 0.05 0 0
Testability
(1/3)
Auditability (1/6) 0.93 0.07 0 0 Complexity (1/6) 0.91 0.06 0.03 0 Since the view (1/6) 0.89 0.1 0.01 0 Modularity (1/6) 0.86 0.12 0.02 0 Security (1/6) 0.92 0.06 0.02 0
Product changes (0.2)
Portability (1/3) Versatility (1/5) 0.91 0.07 0.02 0 Hardware independence (1/5) 0.81 0.14 0.05 0 Modularity (1/5) 0.93 0.05 0.02 0 Security (1/5) 0.91 0.06 0.03 0 Simplicity (1/5) 0.96 0.04 0 0 Reusability (1/3) Versatility (1/5) 0.93 0.05 0.02 0 Hardware independence (1/5) 0.84 0.12 0.04 0 Modularity (1/5) 0.94 0.06 0 0 Security (1/5) 0.87 0.1 0.03 0 Simplicity (1/5) 0.92 0.06 0.02 0 Interoperability (1/3)
Communication in common (1/4)
0.91 0.06 0.03 0 Data in common
(1/4)
0.9 0.15 0.05 0 Versatility (1/4) 0.89 0.11 0 0
Modularity (1/4) 0.92 0.08 0 0
Product operation (0.35)
Accuracy
(1/5) Completeness (1/3) 0.96 0.02 0.02 0 Consistency (1/3) 0.94 0.06 0 0 System independence (1/3) 0.93 0.05 0.02 0 Reliability (1/5) Accuracy (1/6) 0.97 0.03 0 0
Complexity (1/6) 0.95 0.03 0.02 0 Consistency (1/6) 0.81 0.14 0.05 0 Fault tolerance (1/6) 0.91 0.06 0.03 0 Modularity (1/6) 0.97 0.03 0 0 Availability (1/5)
System independence (1/2) 0.86 0.12 0.02 0 Operability (1/2) 0.88 0.1 0.02 0 Efficiency (1/5)Simplicity (1/3) 0.94 0.06 0 0
Performance (1/3) 0.92 0.07 0.01 0
Operability (1/3) 0.90 0.08 0.02 0
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The Comprehensive Evaluation of Software Quality Bad on Fuzzy Theory 254
(1) Determine the t of reviews, t V = {V1, V2, V3, V4} for the reviews t, V1 = “Excellent”, V2 = “good”; V3 = “general”; V4 = “bad”;
(2) Determine the fuzzy evaluation matrix: the first component bad on the evaluation results of the initial evaluation matrix R0. As shown in Table 1 and the corresponding elements of the weight, according to the formula (1) and (3) to calculate an evaluation results, and then form the matrix R1, then according to the formula (4) obtained two results, and evaluation matrix compod of R2.
(3) Comprehensive Evaluation: R2 according to the formula (4) obtained by asssment of software products fuzzy comprehensive evaluation value. Software quality by calculating the final results of the comprehensive evaluation was “Excellent”.
The evaluation results and the actual position, but in digital form that is more preci and specific application of multi-level comprehensive evaluation to be more scientific and accurate information about software quality control, with very good value.
5. Conclusions
This paper prents a theory of software quality bad on fuzzy comprehensive evaluation method, bad on the actual situation, but also raid before the judge to add restrictions. Fuzzy comprehensive evaluation model for software quality control and evaluation of a scientific basis. In the implementation腔调的拼音
榴莲蜜和菠萝蜜的区别of the evaluation process, you can continue to improve
to keep up the pace of the software industry, to enrich and perfect evaluation system, to find the ideal software quality evaluation method of accumulated uful experience.
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