Earticle

The concern of this study is to identify software risks and controls in the software development lifecycle. The aim of this study is to rank the software risks factors according to their importance and occurrence frequency based on the data source. The survey questionnaire is used to collect data and method of sample selection referred to as ‘snowball’ and distribution personal regular sampling was used. The seventy six software project managers have participated in this study who works in the Palestinian software development. Fifty software risk factors in all phases SDLC and thirty risk management techniques were presented to respondents. The results show that all risks in software projects were significant and important in software project manager's perspective. However, the ranking of the importance of the risks is assigned according to it: Analysis, planning, maintenance, design, and implementation. In addition, the top ten software risk factors in software development are selected and used for further analysis such as: Risk13, Risk 14, Risk15, Risk16, Risk11, Risk18, Risk12, Risk50, Risk19, and Risk 9. The concern of this paper the top ten controls are used to model its relationship with the risk, such as: C29, C30, C20, C27, C21, C19, C28, C25, C26, and C23. Software risks can be modelled empirically with risk management control techniques. We recommended applying more studies in software risk management practices with real world companies and building tools to identification and analysis software risks based on quantitative and intelligent techniques.

The aim of this study is to propose the discriminant analysis (DA) techniques to classify and manage risks in software planning development process. These techniques are used to test the controls to each of risks to determine and classify if they are effective in mitigating the occurrence of each risk planning factor. We classified risks to three levels by predicted group membership. Also top ten risks planning software development were mitigated by using controls based on discriminant analysis techniques.

Object-oriented software systems emerge from mere keystrokes to form intricate functional networks connecting many collaborating objects. In this paper, building on complex networks, software collaboration networks contained within several open-source software systems have been examined. Because of the association between objects, the ripple effect exists in those software networks. The distributions of forward and reversal ripple degree in software networks are analyzed, and focusing on high ripple degree nodes, a metric formula that evaluates the significance is presented. According to our metric, the fragile nodes, rigid nodes and a “hidden danger” node in software system can be selected, which can be used to provide guidance for design and remodeling of software systems.

Software is more diverse and complex and the level of importance for the maintenance of application software to securely operate software is also gradually increasing in proportion. The calculation method for maintenance cost of application software applied in Korea public enterprises is involved in the range of 10 to 15% of development cost, depending on the Software Project Cost Estimation Guide. Moreover, as most software maintenance cost estimation procedures do not take into consideration of the risk factors related of maintenance, it can be seen as a main cause for the occurrence of maintenance related accidents. This study proposes a maintenance cost estimate model that takes into consideration of the risks related to the software maintenance activities to improve and resolve issues arising from the estimation of maintenance cost. In doing so, maintenance risk factors are analyzed and a risk index is derived through the analysis of risk levels based on the risk factors. Based on such analysis, a maintenance cost estimate method which reflects the maintenance risk index was established.