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A RIGOROUS APPROACH TO STRUCTURAL-ANALYSIS AND METRICATION OF SOFTWARE

SOFTWARE & MICROSYSTEMS 1985年第1期4卷 2-16页

作者： WHITTY, RW FENTON, NE KAPOSI, AA POLYTECH S BANK DEPT ELECT & ELECTR ENGNLONDON SE1 0AAENGLAND GOLDSMITHS COLL DEPT MATH SCILONDON SE14 6NWENGLAND

The need is argued for a rigorous and general theory of structured programming as a basis for improving software quality. Formal graph theoretic methods are developed which allow the structural modelling, metrication and reconstruction of sequential programs in terms of precisely defined general sets of basic control structures. Throughout, concepts are illustrated by examples based on actual basic and Pascal text.

关键词： software engineering graph theoretic methods sequential programs Pascal software quality structured programming basic control structures metrication of software Systems analysis and programming structural analysis basic

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Cognitive Complexity and Graph Convolutional Approach Over control Flow Graph for Software Defect Prediction

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IEEE ACCESS 2022年 10卷 108870-108894页

作者： Gupta, Mansi Rajnish, Kumar Bhattacharjee, Vandana Birla Inst Technol Mesra Dept Comp Sci & Engn Ranchi 835215 Bihar India

The software engineering community is working to develop reliable metrics to improve software quality. It is estimated that understanding the source code accounts for 60% of the software maintenance effort. Cognitive informatics is important in quantifying the degree of difficulty or the efforts made by developers to understand the source code. Several empirical studies were conducted in 2003 to assign cognitive weights to each possible basic control structure of software, and these cognitive weights are used by several researchers to evaluate the cognitive complexity of software systems. In this paper, an effort has been made to categorize the control Flow Graphs (CFGs) nodes according to their node features. In our case, we extracted seven unique features from the program, and each unique feature was assigned an integer value that we evaluated through Cognitive Complexity Measures (CCMs). We then incorporated CCMs' results as a node feature value in CFGs and generated the same based on the node connectivity for a graph. In order to obtain the feature representation of the graph, a node vector matrix is then created for the graph and passed to the Graph Convolutional Network (GCN). We prepared our data sets using GCN output and then built Deep Neural Network Defect Prediction (DNN-DP) and Convolutional Neural Network Defect Prediction (CNN-DP) models to predict software defects. The Python programming language is used, along with Keras and TensorFlow. Three hundred twenty Python programs were written by our talented UG and PG students, and all experiments were carried out during laboratory classes. Together with three skilled lab programmers, they compiled and ran each individual program and detected defect/no-defect programs before categorizing them into three different classes, namely Simple, Medium, and Complex programs. Accuracy, Receiver Operating Characteristics (ROC), Area Under Curve (AUC), F-measure, Precision and hyper-parameter tuning procedures are used

关键词： Software reliability Complexity theory Deep learning Predictive models Convolutional neural networks Neural networks Feature extraction Cognition Informatics Software quality basic control structures cognitive complexity measures control flow graphs graph convolutional network neural network software defect prediction cognitive informatics

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A cognitive and neural network approach for software defect prediction

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2022年第5期43卷 6477-6503页

作者： Rajnish, Kumar Bhattacharjee, Vandana Birla Inst Technol Dept CSE Ranchi 835215 Bihar India

Software defect prediction is used to assist developers in finding potential defects and allocating their testing efforts as the scale of software grows. Traditional software defect prediction methods primarily concentrate on creating static code metrics that are fed into machine learning classifiers to predict defects in the code. To achieve the desired classifier performance, appropriate design decisions are required for deep neural network (DNN) and convolutional neural network (CNN) models. This is especially important when predicting software module fault proneness. When correctly identified, this could help to reduce testing costs by concentrating efforts on the modules that have been identified as fault prone. This paper proposes a CONVSDP and DNNSDP (cognitive and neural network) approach for predicting software defects. Python Programming Language with Keras and TensorFlow was used as the framework. From three NASA system datasets (CM1, KC3, and PC1) selected from PROMISE repository, a comparative analysis with machine learning algorithms (such as Random Forest (RF), Decision Trees (DT), Nave Bayes (NF), and Support Vector Machine (SVM) in terms of F-Measure (known as F1-score), Recall, Precision, Accuracy, Receiver Operating Characteristics (ROC) and Area Under Curve (AUC) has been presented. We extract four dataset attributes from the original datasets and use them to estimate the development effort, development time, and number of errors. The number of operands, operators, branch count, and executable LOCs are among these attributes. Furthermore, a new parameter called cognitive weight (Wc) of basic control Structure (BCS) is proposed to make the proposed cognitive technique more effective, and a cognitive data set of 8 features for NASA system datasets (CM1, KC3, and PC1) selected from the PROMISE repository to predict software defects is created. The experimental results showed that the CONVSDP and DNNSDP models was comparable to existing classifiers i

关键词： Machine learning software defect prediction CNN model cognitive weight basic control structures neural network

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Comparative Study of Cognitive Complexity Measures

Comparative Study of Cognitive Complexity Measures

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23rd International Symposium on Computer and Information Sciences (ISCIS)

作者： Misra, Sanjay Akman, Ibrahim Atilim Univ Dept Comp Engn Ankara Turkey

ISBN: (纸本)9781424428809

Complexity metrics are used to predict critical information about reliability and maintainability of software systems. Cognitive complexity measure based on cognitive informatics, plays an important role in understanding the fundamental characteristics of software, therefore directly affects the understandability and maintainability of software systems. In this paper, we compared available cognitive complexity measures and evaluated cognitive weight complexity measure in terms of Weyuker's properties.

关键词： Software metrics cognitive weights basic control structures Weyuker's Properties

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Complexity Measurement: A New Approach to Ensure Equal Distribution of Programming Problems for Evaluation 8

Complexity Measurement: A New Approach to Ensure Equal Distr...

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International Conference on Electrical and Computer Engineering

作者： Bashir, G. M. M. Dey, Samrat Kumar Tariq, S. S. M. Islam, Md. Shariful Patuakhali Sci & Technol Univ Dept CCE Patuakhali Bangladesh Patuakhali Sci & Technol Univ Fac CSE Patuakhali Bangladesh

ISBN: (纸本)9781479941667

Distributing equivalent programming problems among the students for evaluation is an inherent problem. To remove this inherent problem, weight measurement of computer programs is necessary. Although software is the outcome of human creative activity, cognitive informatics plays an important role in understanding its fundamental characteristics. In our research, a new software complexity measure based on cognitive weight of basic control structure has been proposed that reduce the limitations of existing measures. Primarily our aim is to build a question bank with programming problems. Our designed system will access the solution codes for finding out the weight of respective programming problem from the question bank by applying the proposed method. The method will find out the complexity according to our proposed cognitive weight model. It will facilitate the instructors distributing the programming problems among the students equivalently. Thus, the automatic complexity measurement will ensure the students obtaining equal problems for programming evaluation.

关键词： Cognitive Weights basic control structures Weight Measurement Software Complexity

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Cognitive program complexity measure

Cognitive program complexity measure

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6th IEEE International Conference on Cognitive Informatics (ICCI 2007)

作者： Misra, Sanjay Atilim Univ Dept Comp Engn Ankara Turkey

ISBN: (纸本)9781424413270

In cognitive informatics, the functional complexity of software depends on three factors: internal architecture, input, and output. In the earlier proposed metrics based on cognitive informatics, these above factors are not fully considered. This paper proposes an improved cognitive complexity measure. Accordingly, new formula is developed to calculate the cognitive complexity. An attempt has also been made to evaluate and validate the proposed measure through Weyuker's properties and a practical framework It has been found that seven of nine Weyuker's properties have been satisfied by the proposed cognitive complexity measure. It also satisfies most of the parameters required by the practical framework hence establishes as a well-structured one. Finally, a comparative study with similar measures has been made to prove its robustness.

关键词： software metrics cognitive weights basic control structures cognitive complexity measures

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An Effective Approach of Evaluating Cognitive Weight and Equivalent Distribution of Programming Problems 2

An Effective Approach of Evaluating Cognitive Weight and Equ...

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2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)

作者： Bashir, Golam Md Muradul Muhtasim, Muhammad Ahmed, Md Monsur Patuakhali Sci & Technol Univ Fac Comp Sci & Engn Patuakhali Bangladesh

ISBN: (纸本)9781665404891

Equal distribution of programming problems among the students is so significant during the examination within limited times. But how could we determine that how student feels about whether a given program is either easy or difficult? So Complexity measurement according to their brain thinking capability is necessary. In this article, we have improved the approach of complexity measurement procedure that gives us more accurate value of cognitive weight which contract the constraints of existing measures. The idea of cognitive weight of any basic control structure is ethically based on the logical capacity of the human brain. As per our cognitive data gathering from various level of students, we have built up a new software tool using Java Standard Edition and MySQL for equivalent distribution of programming problems dependent on our developed algorithm. The problems is categorized according to three difficulty level (simple, medium, hard) for each level of students. This will help instructor allocate problems while maintaining an equivalent level of problems for students.

关键词： Cognitive Weights basic control structures Weight Measurement Equivalent Distribution Programming problems Java SE MySQL Database

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Evaluating cognitive complexity measure with Weyuker properties

Evaluating cognitive complexity measure with Weyuker propert...

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3rd IEEE International Conference on Cognitive Informatics (ICCI 2004)

作者： Misra, S Misra, AK Motilal Nehru Natl Inst Technol Dept Comp Sci & Engn Allahabad Uttar Pradesh India

ISBN: (纸本)0769521908

Cognitive complexity measure is based on Cognitive informatics, which in turn helps in comprehending the software characteristics. Weyuker properties must be satisfied by every complexity measure to qualify as a good and comprehensive one. In this paper an attempt has been made to evaluate cognitive complexity measure in terms of nine Weyuker properties, through examples. It has been found that eight of nine Weyuker properties have been satisfied by the cognitive weight software complexity measure and hence establishes the cognitive complexity as a well structured one.

关键词： cognitive weight basic control structures software complexity software functional size

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Modified cognitive complexity measure

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21st International Symposium on Computer and Information Sciences (ISCIS 2006)

作者： Misra, Sanjay Atilim Univ Dept Comp Engn Ankara Turkey

ISBN: (纸本)3540472428

In cognitive functional size measure, the functional size is proportional to weighted cognitive complexity of all internal BCS's and number of input and output. This paper proposes the modification in cognitive functional size complexity measure. The proposed complexity measure is proportional to total occurrence of operators and operands and all internal BCS's. The operators and operands are equally important in design consideration. Thus, the contribution of the operators, operands and cognitive aspects complete the definition of a complexity measure in terms of cognitive. Accordingly, a new formula is developed for calculating the modified cognitive complexity measure. An attempt has also been made to evaluate modified cognitive complexity measure in terms of nine Weyuker's properties, through examples. It has been found that seven of nine Weyuker's properties have been satisfied by the modified cognitive complexity measure and hence establishes as a well-structured one.

关键词： software metrics cognitive weights basic control structures cognitive complexity measure

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On the big-R notation for describing iterative and recursive behaviors

On the big-R notation for describing iterative and recursive...

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5th IEEE International Conference on Cognitive Informatics (ICCI 2006)

作者： Wang, Yingxu Univ Calgary Dept Elect & Comp Engn Theoret & Empirical Software Engn Res Ctr Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781424404759

The iterative and recursive control structures are the most fundamental mechanisms of computing, because they make programming more effective and expressive. However, these constructs are perhaps the most diverse and confusable instructions in programming languages at both syntactic and semantic levels. Although a wide variety of ways have been proposed for describing iterations, there is still a lack of a unified mathematical notation that may be used to express the notion of repetitive, recursive, and predicative behaviors and architectures in computing.

关键词： computing cognitive informatics basic control structures mathematical notations the big-R notation iteration recursion loop syntax semantics RTPA formal methods

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