Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!ames!henry.jpl.nasa.gov!elroy.jpl.nasa.gov!ucla-cs!lanai!johnny From: johnny@lanai.cs.ucla.edu (Jia Hong Chen) Newsgroups: comp.software-eng Subject: Re: Software Failure Analysis Keywords: Software failure analysis, quantization errors, resolution Message-ID: <27545@shemp.CS.UCLA.EDU> Date: 28 Sep 89 22:01:41 GMT References: <10743@dasys1.UUCP> <34348@regenmeister.uucp> <592@halley.UUCP> <290@cs.nps.navy.mil> Sender: news@CS.UCLA.EDU Reply-To: johnny@lanai.UUCP (Jia Hong Chen) Organization: UCLA CS DEPT. Lines: 38 For ANOTHER view of Knight and Leveson's experiment, one recent paper which might be interesting to you is "Failure Masking: a Source of Failure Dependency in Multi-Version Programs", P. G. Bishop and F. D. Pullen (Central Electricity Research Laboratories, Leatherthead, UK). It appeared in the proceedings of the first International Working Conference on Dependable Computing for Critical Applications at Santa Barbara, August 23-25, 1989. Quotated from the abstract: " .... Error masking behavior can be predicted from the specification (prior to implementation), and simple modifications to the program design can minimize the error masking effect and hence the observed dependency." Prof. Algirdas Avizienis in the question and answer session after the presentation of the paper by Bishop made some comments about the paper. I don't remember the exact words. Basically he mentioned that the "error masking" is another way of saying that if you reduced the resolution of something and make comparisons on the the variable(s) with the resolution reduced, you end up losing something. During the conference, I had chances to visit my friend's (a EE graduate at UCSB) speech lab on campus. He demonstrated to me some of their speech coding (based on Linear Predictive Coding) research, with different bit rates. Intuitively with more bit rates you can provide higher quality sound. But with some algorithms, you might be able to improve the quality with the same bit rate. People who are familiar with the concept of "quantization errors" should have no difficulty understanding the mumblings in the above paragraph. Also, I sort of remember some similar ideas when I studied the D-algorithm back when I was an undergraduate at National Taiwan University. Check out the paper and make up you mind. Don't trust everything published. Jia-Hong Chen johnny@cs.ucla.edu ...!ucbvax!cs.ucla.edu!johnny