JournalTOCs

International Journal of Software Engineering, Technology and Applications
Number of Followers: 4

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2053-2466 - ISSN (Online) 2053-2474
Published by Inderscience Publishers

[439 journals]

A package-based clustering approach to enhance the accuracy and
performance of software defect prediction
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  Authors: Rayhanul Islam, Kazi Sakib
  Pages: 1 - 21
  Abstract: To enhance the accuracy and performance, software defect prediction models considering clustering of dataset combine related and similar features to improve the learning process of the model. Here, a clustering approach named package-based clustering has been proposed to group the similar and related parts of software using object oriented classes' relationships and similarities. To segregate software into clusters, it performs textual analysis to identify all object-oriented classes from source codes. Then it uses package information of each class to divide those into clusters. To analyse the performance of the proposed algorithm, linear regression model is used, which learns from clusters of related and similar classes. The experiment has been conducted on eight releases of two open source software, which are Xalan and Ant, and results show that the proposed technique outperforms the existing clustering algorithms those are BorderFlow and the entire system.
  Keywords: software engineering; software testing; software defect prediction; SDP; package-based clustering; PBC
  Citation: International Journal of Software Engineering, Technology and Applications, Vol. 2, No. 1 (2017) pp. 1 - 21
  PubDate: 2017-10-03T23:20:50-05:00
  DOI: 10.1504/IJSETA.2017.086930
  Issue No: Vol. 2, No. 1 (2017)
Using chemical reaction optimisation for test case minimisation problem
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  Authors: Sudhir Kumar Mohapatra, Srinivas Prasad
  Pages: 22 - 40
  Abstract: The software is modified several times. In regression testing, it is ensured that these modifications in the software never affect the software negatively. The modifications to the software also create new test cases due to the addition of new functionality. These modifications or versions of the software make the test suit size growing over time. Again, re-testing of all the test cases is practically impossible. To avoid re-test all (testing all the test case again), regression test case minimisation (TCM) plays a vital role by reducing the size of the test case. TCM problem is one of the major regression testing problems, which can reduce the cost of regression testing by reducing the size of test case pool. This paper searches the possibility of applying chemical reaction optimisation (CRO) to solve TCM. The developed algorithm is tested with object oriented program of a different line of code (LOC). The simulation results indicate that this algorithm gives an outstanding performance to reduce the test cases and saving object oriented software cost. This reduces test case containing redundant free test cases without compromising on their overall effectiveness.
  Keywords: chemical reaction optimisation; CRO; software testing; test suite minimisation; test case reduction
  Citation: International Journal of Software Engineering, Technology and Applications, Vol. 2, No. 1 (2017) pp. 22 - 40
  PubDate: 2017-10-03T23:20:50-05:00
  DOI: 10.1504/IJSETA.2017.086971
  Issue No: Vol. 2, No. 1 (2017)
Code sniffer: a risk based smell detection framework to enhance code
quality using static code analysis
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  Authors: Ahmad Tahmid, Md. Nurul Ahad Tawhid, Sumon Ahmed, Kazi Sakib
  Pages: 41 - 63
  Abstract: To maintain software and enhance its code quality, code smell, i.e., undesired design flaws need to be detected. However, as the system size increases, manual smell detection becomes difficult. In this paper, a static code analysis framework, named code sniffer, is proposed to detect code smells with predicting their risk severity. This has been calculated using code metrics, and defined as low, moderate and high. The system consists of three main components: parser extracts a syntax tree from the given source code to identify the code structure. The syntax tree is searched against the syntax of class and method. Analyser searches found classes and methods against various code syntax to identify key features like line of code (LOC), number of properties (NOP), etc. In smell and risk detector, code smells, risky code segments and their severity are detected as a set of quantitative values (using LOC, NOP, etc.) using which classes and methods are judged. A comparative case study of this risk based static analyser is performed with a dynamic analyser, FxCop, and the comparison results support each other.
  Keywords: code smell; static analysis; risk based smell detection; code quality
  Citation: International Journal of Software Engineering, Technology and Applications, Vol. 2, No. 1 (2017) pp. 41 - 63
  PubDate: 2017-10-03T23:20:50-05:00
  DOI: 10.1504/IJSETA.2017.086988
  Issue No: Vol. 2, No. 1 (2017)
Exploring the relationships between design measures and change proneness
in object-oriented systems
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  Authors: Deepa Godara, Rakesh Kumar Singh
  Pages: 64 - 80
  Abstract: Managing change early in software development life cycle can lead to good quality software. Developing software requires a huge amount of time and assets. On the other hand, maintenance expenses are higher than development expenses, which are a major cause for concern, especially, for the systems developed with new technologies. Predicting change is an active research area in the field of software engineering. Such predictions can be used to estimate changes from one release of software to the next. This paper explores various parameters and relationships that can be considered in predicting change prone classes. We elaborate dependency approach method which calculates if one class is dependent on other or not, if a class is dependent, dependency value can be calculated using UML 2.0 sequence diagram. Further, we have extracted frequency and popularity feature from an application that can be used for estimating change prone classes. We have related frequency and popularity with dependency in terms of method calling. Also, we have created a tool in Java which generates UML 2.0 sequence diagram and using the sequence diagram dependency value is generated.
  Keywords: frequent item set mining algorithm; software maintenance; dynamic metrics; software development life cycle; frequency; popularity
  Citation: International Journal of Software Engineering, Technology and Applications, Vol. 2, No. 1 (2017) pp. 64 - 80
  PubDate: 2017-10-03T23:20:50-05:00
  DOI: 10.1504/IJSETA.2017.086931
  Issue No: Vol. 2, No. 1 (2017)