Semantic Knowledge Management System to Support Software Engineers: Implementation and Static Evaluation through Interviews at Ericsson

Journal Title: e-Informatica Software Engineering Journal - Year 2018, Vol 12, Issue 1

Abstract

Background: In large-scale corporations in the software engineering context information overload problems occur as stakeholders continuously produce useful information on process life-cycle issues, matters related to specific products under development, etc. Information overload makes finding relevant information (e.g., how did the company apply the requirements process for product X?) challenging, which is in the primary focus of this paper. Contribution: In this study the authors aimed at evaluating the ease of implementing a semantic knowledge management system at Ericsson, including the essential components of such systems (such as text processing, ontologies, semantic annotation and semantic search). Thereafter, feedback on the usefulness of the system was collected from practitioners. Method: A single case study was conducted at a development site of Ericsson AB in Sweden. Results: It was found that semantic knowledge management systems are challenging to implement, this refers in particular to the implementation and integration of ontologies. Specific ontologies for structuring and filtering are essential, such as domain ontologies and ontologies distinct to the organization. Conclusion: To be readily adopted and transferable to practice, desired ontologies need to be implemented and integrated into semantic knowledge management frameworks with ease, given that the desired ontologies are dependent on organizations and domains.

Authors and Affiliations

Ali Demirsoy, Kai Petersen

Keywords

Related Articles

Malicious JavaScript Detection by Features Extraction

In recent years, JavaScript-based attacks have become one of the most common and successful types of attack. Existing techniques for detecting malicious JavaScripts could fail for different reasons. Some techniques are t...

Cross-Project Defect Prediction with Respect to Code Ownership Model: An Empirical Study

The paper presents an analysis of 83 versions of industrial, open-source and academic projects. We have empirically evaluated whether those project types constitute separate classes of projects with regard to defect pred...

A literature review on the effectiveness and efficiency of business modeling

Background: Achieving and maintaining a strategic competitive advantage through business and technology innovation via continually improving effectiveness and efficiency of the operations are the critical survival factor...

Applying Machine Learning to Software Fault Prediction

Introduction: Software engineering continuously suffers from inadequate software testing. The automated prediction of possibly faulty fragments of source code allows developers to focus development efforts on fault-prone...

Tool Features to Support Systematic Reviews in Software Engineering – A Cross Domain Study

Context: Previously, the authors had developed and evaluated a framework to evaluate systematic review (SR) lifecycle tools. Goal: The goal of this study was to use the experiences of researchers in other domains to furt...

Download PDF file
  • EP ID EP382525
  • DOI 10.5277/e-Inf180110
  • Views 84
  • Downloads 0

How To Cite

Ali Demirsoy, Kai Petersen (2018). Semantic Knowledge Management System to Support Software Engineers: Implementation and Static Evaluation through Interviews at Ericsson. e-Informatica Software Engineering Journal, 12(1), 237-263. https://europub.co.uk/articles/-A-382525