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University of Western Ontario

1. Mohamed, Tamer Mohamed Abdellatif. Automatic Recall of Lessons Learned for Software Project Managers.

Degree: 2018, University of Western Ontario

Lessons learned (LL) records constitute a software organization’s memory of successes and failures. LL are recorded within the organization repository for future reference to optimize planning, gain experience, and elevate market competitiveness. However, manually searching this repository is a daunting task, so it is often overlooked. This can lead to the repetition of previous mistakes and missing potential opportunities, which, in turn, can negatively affect the organization’s profitability and competitiveness. In this thesis, we present a novel solution that provides an automatic process to recall relevant LL and to push them to project managers. This substantially reduces the amount of time and effort required to manually search the unstructured LL repositories, and therefore, it encourages the utilization of LL. In this study, we exploit existing project artifacts to build the LL search queries on-the-fly, in order to bypass the tedious manual search process. While most of the current LL recall studies rely on case-based reasoning, they have some limitations including the need to reformat the LL repository, which is impractical, and the need for tight user involvement. This makes us the first to employ information retrieval (IR) to address the LL recall. An empirical study has been conducted to build the automatic LL recall solution and evaluate its effectiveness. In our study, we employ three of the most popular IR models to construct a solution that considers multiple classifier configurations. In addition, we have extended this study by examining the impact of the hybridization of LL classifiers on the classifiers’ performance. Furthermore, a real-world dataset of 212 LL records from 30 different software projects has been used for validation. Top-k and MAP, well-known accuracy metrics, have been used as well. The study results confirm the effectiveness of the automatic LL recall solution by a discerning accuracy of about 70%, which was increased to 74% in the case of hybridization. This eliminates the effort needed to manually search the LL repository, which positively encourages project managers to reuse the available LL knowledge – which in turn avoids old pitfalls and unleash hidden business opportunities.

Subjects/Keywords: Software lessons learned recall; software project management; knowledge management; information retrieval models; software analytics; systematic literature review; Electrical and Computer Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mohamed, T. M. A. (2018). Automatic Recall of Lessons Learned for Software Project Managers. (Thesis). University of Western Ontario. Retrieved from https://ir.lib.uwo.ca/etd/5615

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mohamed, Tamer Mohamed Abdellatif. “Automatic Recall of Lessons Learned for Software Project Managers.” 2018. Thesis, University of Western Ontario. Accessed September 24, 2018. https://ir.lib.uwo.ca/etd/5615.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mohamed, Tamer Mohamed Abdellatif. “Automatic Recall of Lessons Learned for Software Project Managers.” 2018. Web. 24 Sep 2018.

Vancouver:

Mohamed TMA. Automatic Recall of Lessons Learned for Software Project Managers. [Internet] [Thesis]. University of Western Ontario; 2018. [cited 2018 Sep 24]. Available from: https://ir.lib.uwo.ca/etd/5615.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mohamed TMA. Automatic Recall of Lessons Learned for Software Project Managers. [Thesis]. University of Western Ontario; 2018. Available from: https://ir.lib.uwo.ca/etd/5615

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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