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| 2. |
- Al Mamun, Md Abdullah, 1982, et al.
(författare)
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Correlations of software code metrics : An empirical study
- 2017
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Ingår i: IWSM Mensura '17. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450348539 ; , s. 255-266
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Konferensbidrag (refereegranskat)abstract
- Background: The increasing up-trend of software size brings about challenges related to release planning and maintainability. Foreseeing the growth of software metrics can assist in taking proactive decisions regarding different areas where software metrics play vital roles. For example, source code metrics are used to automatically calculate technical debt related to code quality which may indicate how maintainable a software is. Thus, predicting such metrics can give us an indication of technical debt in the future releases of software. Objective: Estimation or prediction of software metrics can be performed more meaningfully if the relationships between different domains of metrics and relationships between the metrics and different domains are well understood. To understand such relationships, this empirical study has collected 25 metrics classified into four domains from 9572 software revisions of 20 open source projects from 8 well-known companies. Results: We found software size related metrics are most correlated among themselves and with metrics from other domains. Complexity and documentation related metrics are more correlated with size metrics than themselves. Metrics in the duplications domain are observed to be more correlated to themselves on a domain-level. However, a metric to domain level relationship exploration reveals that metrics with most strong correlations are in fact connected to size metrics. The Overall correlation ranking of duplication metrics are least among all domains and metrics. Contribution: Knowledge earned from this research will help to understand inherent relationships between metrics and domains. This knowledge together with metric-level relationships will allow building better predictive models for software code metrics. © 2017 Association for Computing Machinery.
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| 3. |
- Al Mamun, Md Abdullah, 1982, et al.
(författare)
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Effects of measurements on correlations of software code metrics
- 2019
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Ingår i: Empirical Software Engineering. - : Springer Science and Business Media LLC. - 1382-3256 .- 1573-7616. ; 24:4, s. 2764-2818
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Tidskriftsartikel (refereegranskat)abstract
- ContextSoftware metrics play a significant role in many areas in the life-cycle of software including forecasting defects and foretelling stories regarding maintenance, cost, etc. through predictive analysis. Many studies have found code metrics correlated to each other at such a high level that such correlated code metrics are considered redundant, which implies it is enough to keep track of a single metric from a list of highly correlated metrics.ObjectiveSoftware is developed incrementally over a period. Traditionally, code metrics are measured cumulatively as cumulative sum or running sum. When a code metric is measured based on the values from individual revisions or commits without consolidating values from past revisions, indicating the natural development of software, this study identifies such a type of measure as organic. Density and average are two other ways of measuring metrics. This empirical study focuses on whether measurement types influence correlations of code metrics.MethodTo investigate the objective, this empirical study has collected 24 code metrics classified into four categories, according to the measurement types of the metrics, from 11,874 software revisions (i.e., commits) of 21 open source projects from eight well-known organizations. Kendall's tau-B is used for computing correlations. To determine whether there is a significant difference between cumulative and organic metrics, Mann-Whitney U test, Wilcoxon signed rank test, and paired-samples sign test are performed.ResultsThe cumulative metrics are found to be highly correlated to each other with an average coefficient of 0.79. For corresponding organic metrics, it is 0.49. When individual correlation coefficients between these two measure types are compared, correlations between organic metrics are found to be significantly lower (with p <0.01) than cumulative metrics. Our results indicate that the cumulative nature of metrics makes them highly correlated, implying cumulative measurement is a major source of collinearity between cumulative metrics. Another interesting observation is that correlations between metrics from different categories are weak.ConclusionsResults of this study reveal that measurement types may have a significant impact on the correlations of code metrics and that transforming metrics into a different type can give us metrics with low collinearity. These findings provide us a simple understanding how feature transformation to a different measurement type can produce new non-collinear input features for predictive models.
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- Al Mamun, Md Abdullah, 1982, et al.
(författare)
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Evolution of technical debt: An exploratory study
- 2019
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Ingår i: CEUR Workshop Proceedings. - : CEUR-WS. - 1613-0073. ; 2476, s. 87-102, s. 87-102
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Konferensbidrag (refereegranskat)abstract
- Context: Technical debt is known to impact maintainability of software. As source code files grow in size, maintainability becomes more challenging. Therefore, it is expected that the density of technical debt in larger files would be reduced for the sake of maintainability. Objective: This exploratory study investigates whether a newly introduced metric ‘technical debt density trend’ helps to better understand and explain the evolution of technical debt. The ‘technical debt density trend’ metric is the slope of the line of two successive ‘technical debt density’ measures corresponding to the ‘lines of code’ values of two consecutive revisions of a source code file. Method: This study has used 11,822 commits or revisions of 4,013 Java source files from 21 open source projects. For the technical debt measure, SonarQube tool is used with 138 code smells. Results: This study finds that ‘technical debt density trend’ metric has interesting characteristics that make it particularly attractive to understand the pattern of accrual and repayment of technical debt by breaking down a technical debt measure into multiple components, e.g., ‘technical debt density’ can be broken down into two components showing mean density corresponding to revisions that accrue technical debt and mean density corresponding to revisions that repay technical debt. The use of ‘technical debt density trend’ metric helps us understand the evolution of technical debt with greater insights.
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| 5. |
- Al Mamun, Md Abdullah, 1982, et al.
(författare)
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Improving Code Smell Predictions in Continuous Integration by Differentiating Organic from Cumulative Measures
- 2019
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Ingår i: The Fifth International Conference on Advances and Trends in Software Engineering. - 2519-8394. - 9781510883741 ; , s. 62-71
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Konferensbidrag (refereegranskat)abstract
- Continuous integration and deployment are enablers of quick innovation cycles of software and systems through incremental releases of a product within short periods of time. If software qualities can be predicted for the next release, quality managers can plan ahead with resource allocation for concerning issues. Cumulative metrics are observed to have much higher correlation coefficients compared to non-cumulative metrics. Given the difference in correlation coefficients of cumulative and noncumulative metrics, this study investigates the difference between metrics of these two categories concerning the correctness of predicting code smell which is internal software quality. This study considers 12 metrics from each measurement category, and 35 code smells collected from 36,217 software revisions (commits) of 242 open source Java projects. We build 8,190 predictive models and evaluate them to determine how measurement categories of predictors and targets affect model accuracies predicting code smells. To further validate our approach, we compared our results with Principal Component Analysis (PCA), a statistical procedure for dimensionality reduction. Results of the study show that within the context of continuous integration, non-cumulative metrics as predictors build better predictive models with respect to model accuracy compared to cumulative metrics. When the results are compared with models built from extracted PCA components, we found better results using our approach.
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| 6. |
- Antinyan, Vard, 1984, et al.
(författare)
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A Complexity Measure for Textual Requirements
- 2016
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Ingår i: Proceedings of 2016 Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement (Iwsm-Mensura). - : IEEE. - 9781509041473 - 9781509041480
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Konferensbidrag (refereegranskat)abstract
- Unequivocally understandable requirements are vital for software design process. However, in practice it is hard to achieve the desired level of understandability, because in large software products a substantial amount of requirements tend to have ambiguous or complex descriptions. Over time such requirements decelerate the development speed and increase the risk of late design modifications, therefore finding and improving them is an urgent task for software designers. Manual reviewing is one way of addressing the problem, but it is effort-intensive and critically slow for large products. Another way is using measurement, in which case one needs to design effective measures. In recent years there have been great endeavors in creating and validating measures for requirements understandability: most of the measures focused on ambiguous patterns. While ambiguity is one property that has major effect on understandability, there is also another important property, complexity, which also has major effect on understandability, but is relatively less investigated. In this paper we define a complexity measure for textual requirements through an action research project in a large software development organization. We also present its evaluation results in three large companies. The evaluation shows that there is a significant correlation between the measurement values and the manual assessment values of practitioners. We recommend this measure to be used with earlier created ambiguity measures as means for automated identification of complex specifications.
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| 7. |
- Antinyan, Vard, 1984, et al.
(författare)
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Identifying Complex Functions : By Investigating Various Aspects of Code Complexity
- 2015
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Ingår i: Proceedings of 2015 Science and Information Conference (SAI). - : IEEE Press. - 9781479985470 - 9781479985487 - 9781479985463 ; , s. 879-888
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Konferensbidrag (refereegranskat)abstract
- The complexity management of software code has become one of the major problems in software development industry. With growing complexity the maintenance effort of code increases. Moreover, various aspects of complexity create difficulties for complexity assessment. The objective of this paper is to investigate the relationships of various aspects of code complexity and propose a method for identifying the most complex functions. We have conducted an action research project in two software development companies and complemented it with a study of three open source products. Four complexity metrics are measured, and their nature and mutual influence are investigated. The results and possible explanations are discussed with software engineers in industry. The results show that there are two distinguishable aspects of complexity of source code functions: Internal and outbound complexities. Those have an inverse relationship. Moreover, the product of them does not seem to be greater than a certain limit, regardless of software size. We present a method that permits identification of most complex functions considering the two aspects of complexities. The evaluation shows that the use of the method is effective in industry: It enables identification of 0.5% most complex functions out of thousands of functions for reengineering.
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| 8. |
- Antinyan, Vard, et al.
(författare)
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Validating software measures using action research a method and industrial experiences
- 2016
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Ingår i: EASE '16. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450336918
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Konferensbidrag (refereegranskat)abstract
- Validating software measures for using them in practice is a challenging task. Usually more than one complementary validation methods are applied for rigorously validating software measures: Theoretical methods help with defining the measures with expected properties and empirical methods help with evaluating the predictive power of measures. Despite the variety of these methods there still remain cases when the validation of measures is difficult. Particularly when the response variables of interest are not accurately measurable and the practical context cannot be reduced to an experimental setup the abovementioned methods are not effective. In this paper we present a complementary empirical method for validating measures. The method relies on action research principles and is meant to be used in combination with theoretical validation methods. The industrial experiences documented in this paper show that in many practical cases the method is effective. © 2016 ACM.
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| 9. |
- Durisic, Darko, 1986, et al.
(författare)
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Addressing the Need for Strict Meta-Modeling in Practice - A Case Study of AUTOSAR
- 2015
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Ingår i: International Conference on Model Driven Engineering and Software Development (MODELSWARD).
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Konferensbidrag (refereegranskat)abstract
- Meta-modeling has been a topic of interest in the modeling community for many years, yielding substantialnumber of papers describing its theoretical concepts. Many of them are aiming to solve the problem of traditionalUML based domain-specific meta-modeling related to its non-compliance to the strict meta-modelingprinciple, such as the deep meta-modeling approach. In this paper, we show the practical use of meta-modelsin the automotive development process based on AUTOSAR and visualize places in the AUTOSAR metamodelwhich are broken according to the strict meta-modeling principle. We then explain how the AUTOSARmeta-modeling environment can be re-worked in order to comply to this principle by applying three individualapproaches, each one combined with the concept of Orthogonal Classification Architecture: UML extension,prototypical pattern and deep instantiation. Finally we discuss the applicability of these approaches in practiceand contrast the identified issues with the actual problems faced by the automotive meta-modeling practitioners.Our objective is to bridge the current gap between the theoretical and practical concerns in meta-modeling.
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| 10. |
- Durisic, Darko, 1986, et al.
(författare)
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Addressing the need for strict meta-modeling in practice - A case study of AUTOSAR
- 2016
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Ingår i: MODELSWARD 2016 - Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development. - : SciTePress. - 9789897581687 - 9789897582325 - 9781509058983 ; , s. 317-322
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Konferensbidrag (refereegranskat)abstract
- Meta-modeling has been a topic of interest in the modeling community for many years, yielding substantial number of papers describing its theoretical concepts. Many of them are aiming to solve the problem of traditional UML based domain-specific meta-modeling related to its non-compliance to the strict meta-modeling principle, such as the deep meta-modeling approach. In this paper, we show the practical use of meta-models in the automotive development process based on AUTOSAR and visualize places in the AUTOSAR metamodel which are broken according to the strict meta-modeling principle. We then explain how the AUTOSAR meta-modeling environment can be re-worked in order to comply to this principle by applying three individual approaches, each one combined with the concept of Orthogonal Classification Architecture: UML extension, prototypical pattern and deep instantiation. Finally we discuss the applicability of these approaches in practice and contrast the identified issues with the actual problems faced by the automotive meta-modeling practitioners. Our objective is to bridge the current gap between the theoretical and practical concerns in meta-modeling. © Copyright 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
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