Software process and product improvement: an empirical assessment

Kuilboer, Jean-Pierre; Ashrafi, Noushin

doi:10.1016/s0950-5849(99)00054-3

Cited by 52 publications

(34 citation statements)

References 8 publications

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“…External factors such as customer satisfaction are only very rarely taken into account in software process improvement projects, see e.g. Kuilboer and Ashrafi (2000). This paper introduces and validates a new concept for software process improvement, i.e.…”

Section: Introductionmentioning

confidence: 89%

Entropy based software processes improvement

et al. 2008

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Actual results of software process improvement projects show different levels of success. Although many software development organisations have adopted improvement models such as CMMI, it appears to be difficult to improve software development processes in the right way, e.g. tuned to the actual needs of the organisation. This paper presents a new approach to determine the direction of improvement for an organisation. This approach is based on an elaboration of the concept of entropy. The approach is empirically validated by carrying out interviews in 11 software development organisations in The Netherlands. The results of the research show that software development organisations can be classified and can be positioned on the basis of their internal and external entropy, c.q. the level of (dis)order in the business system and its environment. Based on a possible out-of-balance situation between the internal and external entropy, directions for software process improvement can be discussed. As such the proposed approach can support the application of current software process improvement methodologies such as the CMMI.

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Section: Introductionmentioning

confidence: 89%

Entropy based software processes improvement

et al. 2008

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“…Using, e.g., predictive or process models that require large amounts of project data as input, or using simulation, can support practitioners (Abdel-Hamid and Madnick 1991), but transparency and, ultimately, trust can be an issue. In addition, the cost of keeping highquality/high-accuracy data for every project up-to-date, making it suitable for input to the prediction simulation, again becomes a problem, as high initiation and maintenance costs increase the initiation threshold of any process improvement activity (Calvo-Manzano Villalón et al 2002;Kuilboer and Ashrafi 2000;Reifer 2000).…”

Section: Background and Related Workmentioning

confidence: 99%

Tool support for disseminating and improving development practices

Ivarsson

Gorschek

2011

Software Qual J

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Knowledge management in software engineering and software process improvement activities pose challenges as initiatives are deployed. Most existing approaches are either too expensive to deploy or do not take an organization's specific needs into consideration. There is thus a need for scalable improvement approaches that leverage knowledge already residing in the organizations. This paper presents tool support for an Experience Factory approach for disseminating and improving practices used in an organization. Experiences from using practices in development projects are captured in postmortems and provide iteratively improved decision support for identifying what practices work well and what needs improvement. An initial evaluation of using the tool for organizational improvement has been performed utilizing both academia and industry. The results from the evaluation indicate that organizational characteristics influence how practices and experiences can be used. Experiences collected in postmortems are estimated to have little effect on improvements to practices used throughout the organization. However, in organizations where different practices are used in different parts of the organization, making practices available together with experiences from use, as well as having context information, can influence decisions on what practices to use in projects.

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“…CMMI for example, has been found too heavy to use by several organizations [12]. And there are others who say that extensive software process improvement (SPI) frameworks, such as CMMI and ISO/IEC 15504 (SPICE) [13] are too large to implement, or even comprehend [14] [15]. For example, a typical CMM SPI cycle can take between one and a half and two years to complete.…”

Section: Variance Of Maturity Modelsmentioning

confidence: 99%