Perspectives on reusing codified project knowledge: a structured literature review

Coners, André; Matthies, Benjamin

doi:10.12821/ijispm060202

Cited by 3 publications

(3 citation statements)

References 76 publications

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“…In Abid et al [25], the authors used the Apriori algorithm to generate association rules that link source code and interface-level metrics with the quality of service. [26] argued that project documentation represents a valuable source of knowledge in project-based organizations. However, reusing knowledge encoded in design documents in future projects is not easy.…”

Section: Knowledge Discovery In Databasesmentioning

confidence: 99%

Improving the evaluation of change requests using past cases

Mello

Fontoura

2023

IJISPM

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As one of the leading causes of project failures, requirements changes are inevitable in any software project. Hence, we propose an intelligent approach to facilitate the risk analysis of a change request by providing information about past cases found in similar change requests, the solutions adopted, and a support tool. The proposed approach uses case-based reasoning to retrieve previous cases similar to the current case. This approach also uses association rules to analyze patterns in the dataset and calculate the probability of risks associated with change requests. We prepared a case study to validate the proposal by analyzing the most frequent challenges in change management and considering how it can solve or minimize such problems. Results show that the proposed approach successfully assists decision-making, predicts potential risks, and suggests coherent solutions to the user. We have developed a support tool to evaluate this approach in practice with experts and obtained four different outcomes. Only a small set of cases failed to provide relevant results to the user. The use of case-based reasoning and association rules has proven to be advantageous in change management despite validity threats associated with the small number of test cases and experts involved.

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Section: Knowledge Discovery In Databasesmentioning

confidence: 99%

Improving the evaluation of change requests using past cases

Mello

Fontoura

2023

IJISPM

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“…The identified risks, the occurred risk events, and their consequences within each project constitute the tacit knowledge kept by individuals. However, given the high staff turnover in the construction industry, critical knowledge for risk management rooted in individuals' minds and experiences may be lost (Coners & Matthies, 2018). To solve the problem, all this risk-related knowledge needs to be captured and then retained in the organizational risk repository so that it can be transferred to organizational knowledge (Eken et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Risk Causation Model to Capture and Transfer Knowledge in International Construction Projects

Zhu

2022

Journal of Civil Engineering and Management

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International construction projects are facing various severe risks from country, partner, company, and project. Global contractors have suffered heavy losses. Previous researches have proved that an available organizational risk repository is a reliable knowledge source that can be used to introduce experience-based solutions of how specific risks can be managed in international construction projects. The construction of the organizational risk repository calls for an effective feedback mechanism that dispels the organizational culture of unwillingness to disclose management failure and encourages proactive creation and retention of data and information on historical projects and risk-related knowledge. Hence, this paper proposes a risk causation model for international construction projects (RCM_ICP) to support such a mechanism. RCM_ICP links response measures to the chain of risks to identify management failures and conduct modifications, thereby promoting thinking on the part of the management and capturing key risk management experiences. It includes a category component for the efficient retrieval of relevant knowledge based on country-related factors. Besides, this paper proposes the risk review procedures as the instruction of RCM_ICP. Hence, this research breaks the barriers of sharing information between project and organization levels in a project-based industry.

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“…In general, maintenance (or actions taken after the first implementation) is an important aspect of a project's lifecycle [4] and as well as an important aspect of project management [5]. While project documentation can represent a valuable source of knowledge, it has been noted that the knowledge codified in project documents is typically not re-used in future projects [6]. Hence, project documentation, while helpful, is not sufficient for a team to maintain an application.…”

Section: Introductionmentioning

confidence: 99%

MIDST: an enhanced development environment that improves the maintainability of a data science analysis

Saltz

Crowston

Heckman

et al. 2021

IJISPM

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With the increasing ability to generate actionable insight from data, the field of data science has seen significant growth. As more teams develop data science solutions, the analytical code they develop will need to be enhanced in the future, by an existing or a new team member. Thus, the importance of being able to easily maintain and enhance the code required for an analysis will increase. However, to date, there has been minimal research on the maintainability of an analysis done by a data science team. To help address this gap, data science maintainability was explored by (1) creating a data science maintainability model, (2) creating a new tool, called MIDST (Modular Interactive Data Science Tool), that aims to improve data science maintainability, and then (3) conducting a mixed method experiment to evaluate MIDST. The new tool aims to improve the ability of a team member to update and rerun an existing data science analysis by providing a visual data flow view of the analysis within an integrated code and computational environment. Via an analysis of the quantitative and qualitative survey results, the experiment found that MIDST does help improve the maintainability of an analysis. Thus, this research demonstrates the importance of enhanced tools tohelp improve the maintainability of data science projects.

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Perspectives on reusing codified project knowledge: a structured literature review

Cited by 3 publications

References 76 publications

Improving the evaluation of change requests using past cases

Improving the evaluation of change requests using past cases

Risk Causation Model to Capture and Transfer Knowledge in International Construction Projects

MIDST: an enhanced development environment that improves the maintainability of a data science analysis

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