IJPTT

Quality Measurement Challenges for Artificial Intelligence Software

	International Journal of Computer & Organization Trends  (IJCOT)
	© 2017 by IJCOT Journal
	Volume - 8 Issue - 1
	Year of Publication : 2018
	Authors :  Zafar Ali

Citation

Zafar Ali "Quality Measurement Challenges for Artificial Intelligence Software", International Journal of Computer & organization Trends (IJCOT), V8(1):1-7 January - February  2018, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.

Abstract In this paper, various metrics of software measurements are explained with examples. The standards developed for software measurement is described. The goals of these standards are also explained. The challenges of quality measurement for AI software are discussed here. AI software is different from the common software in two ways: it generally solves different kind of problems and it solves the problems in a very different way. AI software generally comes with a vague or a quickly changing requirement list. Quality measurement becomes meaningless as how far the objective has been achieved cannot be decided when the objective itself is not clear. Rapid prototyping and freezing of requirements is a short term measure for this issue. The other option is to identify the modules that can be implemented by conventional software and to integrate the measurement plan of all these modules with suitable modifications. Another issue is; AI software is often implemented in a heuristic manner that gives a poor readability and measurement problems. Further a conflict between the prejudiced human being as a tester and tolerant expert system may take place. Ultimate goal of development of expert system is to provide solutions to problems impossible for normal human beings. Future research trends, both long and short term, are briefed here.

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Keywords
artificial-intelligence, software, quality, measurement.