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Reseach Article

An Evidence-based Approach to Discovery and Assessment of Software Engineering Decisions

Published on November 2012 by Priyanka Mathur, Swati V. Chande
Issues and Challenges in Networking, Intelligence and Computing Technologies
Foundation of Computer Science USA
ICNICT - Number 2
November 2012
Authors: Priyanka Mathur, Swati V. Chande
0bf30658-cb6e-4080-b547-1d4edcee0a98

Priyanka Mathur, Swati V. Chande . An Evidence-based Approach to Discovery and Assessment of Software Engineering Decisions. Issues and Challenges in Networking, Intelligence and Computing Technologies. ICNICT, 2 (November 2012), 30-36.

@article{
author = { Priyanka Mathur, Swati V. Chande },
title = { An Evidence-based Approach to Discovery and Assessment of Software Engineering Decisions },
journal = { Issues and Challenges in Networking, Intelligence and Computing Technologies },
issue_date = { November 2012 },
volume = { ICNICT },
number = { 2 },
month = { November },
year = { 2012 },
issn = 0975-8887,
pages = { 30-36 },
numpages = 7,
url = { /specialissues/icnict/number2/9026-1035/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Issues and Challenges in Networking, Intelligence and Computing Technologies
%A Priyanka Mathur
%A Swati V. Chande
%T An Evidence-based Approach to Discovery and Assessment of Software Engineering Decisions
%J Issues and Challenges in Networking, Intelligence and Computing Technologies
%@ 0975-8887
%V ICNICT
%N 2
%P 30-36
%D 2012
%I International Journal of Computer Applications
Abstract

An Evidence-based approach is using a best available evidence for making a judicious decision about a given set of problem. Evidence-based approach is an integration of individually gained expertise with the best possible evidence available from a systematic research. It started in medicine as evidence-based medicine (EBM) and is now being used in other fields such as nursing, psychology, education, library and information science also. Its basic principles are that all practical decisions made should 1) be based on research studies and 2) that these research studies are selected and interpreted according to some specific norms characteristic for Evidence Based Practice [EBP]. Software draws its roots from EBM and does Evidence Based Software Engineering [EBSE] which is potentially important because of the central place software intensive systems are starting to take in everyday life. In Evidence-based software engineering [EBSE], all the experiences are properly documented in order to inform software practice adoption decisions. In EBSE, the study factor would be the technology of interest. The technological specifications should be very detailed and not at a very high level of abstraction that is the software lifecycle and all the design methods should be properly read and documented and only then should the engineer collect evidences on it and design the software generation model. Evidence based software engineering can be applied in testing and cost estimation. Various metaheuristic search techniques are applied for searching literature and relevant evidences are gathered, these evidences are then put into practice. The results are compared with existing practices.

References
  1. www. Human brain. org
  2. Sackett, D. L. ,Straus, S. E. , Richardson,W. S. ,Rosenberg,W. , and Haynes,R. B. Evidence-Based Medicine: How to Practice and Teach EBM, Second Edition, Churchill Livingstone: Edinburgh, 2000.
  3. www. agile. csc. ncsu. edu
  4. B. A. Kitchenham, T. Dybå, M. Jørgensen, Evidence-based software engineering, in: Proceedings of the 26th International Conference on Software Engineering, (ICSE'04), IEEE Computer Society, Washington DC, USA, 2004, pp. 273–281.
  5. M. V. Zelkowitz, D. R. Wallace, and D. W. Binkley, "Experimental Validation of New Software Technology," Lecture Notes on Empirical Software Engineering, World Scientific, 2003, pp. 229–263
  6. www. dur. ac. uk/ebse
  7. B. A. Kitchenham, T. Dybå, M. Jørgensen, Evidence-based software engineering: Proceedings of the 26th International Conference on Software Engineering, (ICSE'04), IEEE Computer Society, Washington DC, USA, 2004, pp. 273–281.
  8. Sackett, D. L. , Straus, S. E. , Richardson, W. S. , Rosenberg, W. , And Haynes, R. B. Evidence-Based Medicine: How to Practice and Teach EBM, Second Edition, Churchill Livingstone: Edinburgh, 2000.
  9. Gada Kadoda, Michelle Cartwright, Liguang Chen, and Martin Shepperd in Experiences Using Case-Based Reasoning to Predict Software Project Effort, 2000 - decgradschool. bournemouth. ac. uk
  10. Juristo, N. , Moreno, A. , Vegas, S. & Solari, M. (2006), 'In search of what we experimentally know about unit testing', IEEE Software 23(6), 72–80
  11. W. Afzal et al. , A systematic review of search-based testing for non-functional system properties, Inform. Softw. Technol. (2009)
  12. Sarvnaz Karimi Falk Scholer SIGIR Workshop on " Supporting Complex Search Tasks"July 28, 2011, Beijing.
  13. B. A. Kitchenham, Guidelines for performing systematic literature reviews in software engineering, Tech. Rep. , EBSE-2007-001, UK (July 2007).
  14. Adapted from "A systematic review of search-based testing for non-functional system properties" Wasif Afzal , Richard Torkar, Robert Feldt
Index Terms

Computer Science
Information Sciences

Keywords

Evidence Based Approach Contentious Decisions Evidence Based Software Engineering Level Of Abstraction Testing And Cost Estimation Metaheuristic Search Techniques