Decision Support System for Risk Assessment and Management Strategies in Distributed Software Development | Zendy

Adeel Aslam | Zendy; Naveed Ahmad | Zendy; Tanzila Saba | Zendy; Abdulaziz S. Almazyad | Zendy; Amjad Rehman | Zendy; Adeel Anjum | Zendy; Abid Khan | Zendy

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Decision Support System for Risk Assessment and Management Strategies in Distributed Software Development

Author(s) -

Adeel Aslam,

Naveed Ahmad,

Tanzila Saba,

Abdulaziz S. Almazyad,

Amjad Rehman,

Adeel Anjum,

Abid Khan

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2757605

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Risk management in distributed software development (DSD) is a well-researched area, providing different methods for assessing risks and suggesting control strategies. However, some of these methods are narrow in scope, only considering few risks, and are too complex to be used in practice whereas others provide many rules and guidelines which are often implicit. Moreover, the knowledge related to risks in DSD is scattered over different publications which make it difficult to find relevant information to be used in practice. This research aims to develop an automated decision support system to aid practitioners in assessing risks and deciding on suitable control strategies. In order to construct the knowledge base for the proposed decision support system, a systematic literature review (SLR) is conducted. Results of SLR are used to identify required questions, options and set of rules to implement our decision support system (DSS). In total 80 studies were identified from which 49 aspects, 53 questions, and a set of rules are extracted. DSS is evaluated through multiple case studies. The results indicate that the developed DSS supports decision-making process in risk assessment and selection of control strategy.

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