Exploring Software Project Planning through Effort Uncertainty in Large Software Projects : An Industrial Case Study

Sammanfattning: Background. Effort estimation is today a crucial part of software development planning. However, much of the earlier research has been focused on the general conditions of effort estimation. Little to no effort has been spent on solution verification (SV) of the projects. It is not surprising considering that SV becomes more relevant, the larger the project. To improve effort estimation, it is key to consider the uncertainties from the assumptions and conditions it relies on. Objectives. The main objective of this study is to identify differences and similarities between general effort estimation and effort estimation in SV in order to find potential improvements to software project planning of large projects. More specifically, this thesis aims to identify what and how activities and factors affect effort uncertainty and what theory and methods can be applied to increase the accuracy of effort estimation in SV. Methods. An exploratory case study was conducted to reach the objectives. It was designed accordingly to the triangulation method and consisted of unstructured interviews, a questionnaire, and archival research. The analysis followed a four steps procedure. First, it aimed to identify each SV activity’s contribution to effort and effort uncertainty. Secondly, identify and analyze which and how factors impact the identified activities. Third, investigate the factors that impact effort uncertainty. Fourth and last, an analysis of how the factors and sources of uncertainty could be used to improve software project planning. Results. The result shows that the activities could be divided into two different groups, based on their difference in contribution to effort and effort uncertainty. The two activities showing a higher uncertainty than effort were trouble report handling& troubleshooting, which is by far the most uncertainty-causing, and fault correction lead-time. The fault-related factors were both collectively and non-collectively found to be the most uncertainty-causing. Furthermore, it showed that the type of product and what type of objective the employee has influenced the cause of uncertainty. Conclusions. The SV process shifts from a proactive and structured way to a more reactive and unstructured way of working with the project life cycle. Moreover, size is not a cause of uncertainty of effort, but the differences in products create different causes. It was concluded that to most effectively address inaccuracy in effort estimation, one should address the activities that constitute a minority in effort but the majority of uncertainty. The most straightforward approach to increase the performance of effort estimation in SV would be to evaluate the inclusion of fault prediction and fault correction. Consequently, the implementation of uncertainty identification and prevention methods such as the six Ws framework and the bottom-up/top-down effort estimation practices.