Online ISSN
1751-8814
Print ISSN
1751-8806
IET Software
Volume 6, Issue 6, December 2012
Volumes & issues:
Volume 6, Issue 6
December 2012
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- Author(s): V. Khatibi Bardsiri ; D.N.A. Jawawi ; S.Z.M. Hashim ; E. Khatibi
- Source: IET Software, Volume 6, Issue 6, p. 461 –473
- DOI: 10.1049/iet-sen.2011.0210
- Type: Article
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Software development effort is one of the most important metrics that must be correctly estimated in software projects. Analogy-based estimation (ABE) and artificial neural networks (ANN) are the most popular methods used widely in this field. These methods suffer from inconsistent and irrelevant projects that exist in the software project datasets. In this paper, a new hybrid method is proposed to increase the accuracy of development effort estimation based on the combination of fuzzy clustering, ABE and ANN methods. In the proposed method, the effect of irrelevant and inconsistent projects on estimates is decreased by designing a new framework, in which all the projects are clustered. The quality of training in ANN and the consistency of historical data in ABE are improved using the proposed framework. Two large and real datasets are utilised in order to evaluate the performance of the proposed method and the obtained results are compared to eight other estimation methods. The promising results showed that the proposed method outperformed the other methods on both datasets. The performance metrics of mean magnitude of relative error (MMRE) and the percentage of the prediction (PRED) (0.25) have been improved by average of 51 and 127% in the first dataset, as well as 52 and 94% in the second dataset. - Author(s): M. Kalita and T. Bezboruah
- Source: IET Software, Volume 6, Issue 6, p. 474 –478
- DOI: 10.1049/iet-sen.2011.0136
- Type: Article
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Investigations on implementation of web application with different techniques are essential for developers’ as well as users’ perspective. As such, the authors propose to investigate the same by implementing two prototype research web applications based on two different implementation techniques. One of the web applications has been implemented based on the Microsoft .NET technique and the other based on the Java technique. Our objective is to carry out a detailed comparative study of both the techniques in terms of efficiency, reliability, performance, scalability, stability and time to market features of both the techniques. Load and stress testing are performed for both the web applications using Mercury LoadRunner. The statistical analysis of recorded data for both the applications is carried out to study the feasibility of the work. In this study, the authors present in detail the results of the authors’ comparative study on the two techniques. - Author(s): C. Jin ; S.-W. Jin ; J.-M. Ye
- Source: IET Software, Volume 6, Issue 6, p. 479 –487
- DOI: 10.1049/iet-sen.2011.0138
- Type: Article
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The identification of a module's fault-proneness is very important for minimising cost and improving the effectiveness of the software development process. How to obtain the relation between software metrics and a module's fault-proneness has been the focus of much research. One technical challenge to obtain this relation is that there is relevance between software metrics. To overcome this problem, the authors propose a reduction dimensionality phase, which can be generally implemented in any software fault-prone prediction model. In this study, the authors present applications of artificial neural network (ANN) and support vector machine in software fault-prone prediction using metrics. A new evaluation function for computing the contribution of each metric is also proposed in order to adapt to the characteristics of software data. The vital characteristic of this approach is the automatic determination of ANN architecture during metrics selection. Four software datasets are used for evaluating the performance of the proposed model. The experimental results show that the proposed model can establish the relation between software metrics and modules’ fault-proneness. Moreover, it is also very simple because its implementation requires neither extra cost nor expert's knowledge. The proposed model has good performance, and can provide software project managers with trustworthy indicators of fault prone components. - Author(s): J. Feigenspan ; M. Schulze ; M. Papendieck ; C. Kästner ; R. Dachselt ; V. Köppen ; M. Frisch ; G. Saake
- Source: IET Software, Volume 6, Issue 6, p. 488 –501
- DOI: 10.1049/iet-sen.2011.0172
- Type: Article
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Software product line (SPL) engineering provides an effective mechanism to implement variable software. However, using preprocessors to realise variability, which is typical in industry, is heavily criticised, because it often leads to obfuscated code. Using background colours to highlight code annotated with preprocessor statements to support comprehensibility has proved to be effective, however, scalability to large SPLs is questionable. The authors’ aim is to implement and evaluate scalable usage of background colours for industrial-sized SPLs. They designed and implemented scalable concepts in a tool called FeatureCommander. To evaluate its effectiveness, the authors conducted a controlled experiment with a large real-world SPL with over 99 000 lines of code and 340 features. They used a within-subjects design with treatment colours and no colours. They compared correctness and response time of tasks for both treatments. For certain kinds of tasks, background colours improve program comprehension. Furthermore, the subjects generally favour background colours compared with no background colours. In addition, the subjects who worked with background colours had to use the search functions less frequently. The authors show that background colours can improve program comprehension in large SPLs. Based on these encouraging results, they continue their work on improving program comprehension in large SPLs. - Author(s): L. Major ; T. Kyriacou ; O.P. Brereton
- Source: IET Software, Volume 6, Issue 6, p. 502 –513
- DOI: 10.1049/iet-sen.2011.0125
- Type: Article
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Teaching programming to novices is a difficult task due to the complex nature of the subject, the negative stereotypes are associated with programming and because introductory programming courses often fail to encourage student understanding. This study investigates the effectiveness of using robots as tools in the teaching of introductory programming and to determine whether such technology can help to overcome the current barriers for learners in this context. The systematic literature review (SLR) methodology is used to address this aim. Nine electronic databases, the proceedings from six conferences and two journals were searched for relevant literature and exclusion criteria, and after performing several validation exercises, in total, 75% of included papers report that robots are an effective teaching tool and can help novice programmers in their studies. Most of these papers focus on the use of physical robots, however, and further research is needed to assess the effectiveness of using simulated robots. - Author(s): L. Xiong ; Q. Tan ; Z. Shao
- Source: IET Software, Volume 6, Issue 6, p. 514 –523
- DOI: 10.1049/iet-sen.2011.0135
- Type: Article
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Soft errors can affect system reliability by influencing software execution. Dynamic implementation for software-based soft error tolerance methods can protect more types of codes; hence, the method can cover more soft errors. Based on the background of dynamic soft error tolerance, this study proposes an approach to analyse dynamic software behaviours under the effects of soft errors. The authors use a special program model that combines abstract computing on the high level with computing of instructions on the low level. On the high level, programs are divided with the granularity of function. On the low level, every function is implemented by the instructions. Those effects of soft errors on instructions on the low level are passed to the computing results of function on the high level. Backed by the computing results of function on the high level, the caused instruction errors that can lead to incorrect program outcome are distinguished within a function. Based on those different level software behaviours with our program model, the dynamic program reliability model is built under the effects of soft errors. From the dynamic program reliability model, we can see the relationship between the characteristics of dynamic program and reliability of dynamic program under the effects of soft errors. Finally, the experimental results of the authors fault injection experiments validate the dynamic program reliability model. In addition, the experimental results also demonstrate the authors analyses of different dynamic software behaviours under the effects of soft errors. - Author(s): T.R. Gopalakrishnan Nair ; V. Suma ; P. Kumar Tiwari
- Source: IET Software, Volume 6, Issue 6, p. 524 –535
- DOI: 10.1049/iet-sen.2011.0148
- Type: Article
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Production of high-quality software is the exquisite need for accomplishing absolute customer satisfaction in software industry. Effective defect management is one of the crucial factors enabling successful development of high-quality products. Inspection and testing are two established methods of defect management domain. However, existing industry atmosphere is not stringent on the quantification of quality of process and people, in order to realise the prime objective of effective defect management. Consequently, defect capturing ability of the process and the efficacy of people are anecdotal leading towards defect manifestation and propagation during different software development stages. This study provides a case study involving empirical analysis of projects from a leading product-based software industry. The investigation strongly indicates the need for awareness and use of quality measurement of process and people in realising effective defect management. Implementation of two recently introduced quality metrics depth of inspection, a process metric and inspection performance metric, a people metric enable the developing team to generate high-quality software. The comprehension of these pair metrics in software development further augments the quality and productivity. It also reduces the expensive rework time, cost and rebinding of resources. Implementation of duo metrics reflects the persistent process improvement of the software enterprise and the resultant success. - Author(s): G.M. Kapitsaki
- Source: IET Software, Volume 6, Issue 6, p. 536 –548
- DOI: 10.1049/iet-sen.2012.0016
- Type: Article
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Context-awareness is related to the application capability to respond proactively to environment conditions. The reuse of existing components is an important challenge in the development of context-aware applications. Web services (WSs), usually exploited in this field acting either as business services by providing specific functionality or as context sources by exposing the retrieval of context information, need to be discovered and matched. In this study, the matchmaking of WSs for the identification of potential context sources is proposed. Descriptions are matched based on context adaptation cases, whereas the process is based on adequate WS descriptions that derive from the proposed semantic WS profile. The procedure is illustrated through a proof of concept based on service descriptions retrieved from online service registries. - Author(s): D. Gray ; D. Bowes ; N. Davey ; Y. Sun ; B. Christianson
- Source: IET Software, Volume 6, Issue 6, p. 549 –558
- DOI: 10.1049/iet-sen.2011.0132
- Type: Article
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Background: The NASA metrics data program (MDP) data sets have been heavily used in software defect prediction research. Aim: To highlight the data quality issues present in these data sets, and the problems that can arise when they are used in a binary classification context. Method: A thorough exploration of all 13 original NASA data sets, followed by various experiments demonstrating the potential impact of duplicate data points when data mining. Conclusions: Firstly researchers need to analyse the data that forms the basis of their findings in the context of how it will be used. Secondly, the bulk of defect prediction experiments based on the NASA MDP data sets may have led to erroneous findings. This is mainly because of repeated/duplicate data points potentially causing substantial amounts of training and testing data to be identical. - Author(s): I. Antović ; S. Vlajić ; M. Milić ; D. Savić ; V. Stanojević
- Source: IET Software, Volume 6, Issue 6, p. 559 –573
- DOI: 10.1049/iet-sen.2011.0060
- Type: Article
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The aim of this study is to identify the correlations between the use case model, data model and the desired user interface (UI). Since use cases describe the interaction between the users and the system, implemented through the user interface with the aim to change the state of the system, the correlation between these three components should be taken into account at the software requirements phase. In this study, the authors have introduced the meta-model of software requirements developed on the identified correlations. Based on this meta-model, it is possible to create a model of concrete software requirements, which enables not only the design and implementation of the user interface, but also the automation of this process. In order to prove the sustainability of this approach, they have developed a special software tool that performs the transformation of the model to an executable source code. They have considered different ways of user interaction with the system, and consequently, they have recommended the set of most common user interface templates. Thus the flexibility of the user interface is achieved, as the user interface of the same use case could be displayed in several different ways, while still maintaining the desired functionality.
Increasing the accuracy of software development effort estimation using projects clustering
Investigations on implementation of web applications with different techniques
Artificial neural network-based metric selection for software fault-prone prediction model
Supporting program comprehension in large preprocessor-based software product lines
Systematic literature review: teaching novices programming using robots
Exploration of the effects of soft errors from dynamic software behaviours
Significance of depth of inspection and inspection performance metrics for consistent defect management in software industry
Web service matchmaking for the development of context-aware applications
Reflections on the NASA MDP data sets
Model and software tool for automatic generation of user interface based on use case and data model
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