Information and Computing Sciences Colloquium

Model-Driven Ethical, Social and Environmental Accounting & Multi-Criteria Decision-Making in Software Production

Vijanti RamautarSiamak Farshidi

Date: 16:00 – 16:30, Thursday, 01.10.2020
Location: Teams ICS Colloquium

Title: Model-Driven Ethical, Social and Environmental Accounting
Abstract: Ethical, social and environmental accounting (ESEA) is the practice of assessing an organisation’s performance in ethical, social and environmental topics. Usually, the results are published in a sustainability report. The surplus of ESEA methods and tools, is causing managerial problems, affecting the identity of social enterprises and complicating policy making. During my talk I will explain how we aim at offering a fresh perspective from which researchers investigate, practitioners apply and policy-makers regulate ESEA. I will discuss our domain-specific modelling language, created to specify existing ESEA methods, and our run-time model interpreter, which can interpret and execute the method models.

Title: Multi-Criteria Decision-Making in Software Production
Abstract: Software producing organizations are constantly making complex decisions, for instance about acquiring new components for their products. Such decisions require significant amounts of knowledge regarding decision domains. As software engineers are not experts in every field, they need to invest a considerable portion of their time in acquiring knowledge regarding each decision domain. Additionally, they need to keep their knowledge always up-to-date because of the provisional and volatile nature of knowledge in the software engineering field. In this study, we present the development process of a theoretical framework that models decision problems in software production. We believe that tracking and documenting the development process of a framework leads to more transparency and increase repeatability of interpretive research. The framework was instantiated to build decision models for six complex decision problems. Furthermore, we designed, implemented, and evaluated a decision support system for storing the decision models and organizing the acquired knowledge. The applicability and validity of the framework have been tested by conducting 19 industry case studies and 89 expert interviews. The software engineers who participated in this research stated that the framework and the decision support system facilitate decision-making, support them with their daily decision problems, and reduce the time and cost of the decision-making process.