At IBM's Watson lab, our team did some work in OPS5 with the RETE algorithm. The resulting program was called an expert system. The team then continued with a

At IBM's Watson lab, our team did some work in OPS5 with the RETE algorithm. The resulting program was called an expert system. The team then continued with a new programming language, YES/L1. Using DeRemer's LALR work in parsing, YES/L1 was a preprocessor to IBM's language PL/I. The language had extensions for expert system rules, and that was based on the RETE algorithm. We IBM made YES/L1 an IBM Program Product, their highest quality software product category, with name KnowledgeTool. Our team worked with GM to make a deployment. We wrote several papers and gave one at an AAAI IAAI conference at Stanford. The work continued with Resource Object Data Manager (RODM). The role of RODM was automation for system and network monitoring and management. So, RODM was some active storage that sat between (A) some target systems in a network or server farm and (B) some managing systems for the target systems. For this work, RODM permitted building software objects. The objects were in an inheritance hierarchy. Each object had fields for data and methods with code. The intention was that the code would be rules written in KnowledgeTool. The objects in RODM were dynamic in that they could be changed, say, roughly like files and directories in a traditional hierarchical file system, during execution. There was use of Ronald Fagin, Jurg Nievergelt, Nicholas Pippenger, H. Raymond Strong, 'Extendible hashing—a fast access method for dynamic files', "ACM Transactions on Database Systems", ISSN 0362-5915, Volume 4, Issue 3, September 1979, Pages: 315 - 344. for keeping track of the names and Cartesian trees for dynamic storage management. RODM had transactional integrity with automatic deadlock detection and resolution. The role of RODM was (A) have a place to write software for system and network automation, (B) have tools, infrastructure, etc. such code needed readily available, (C) be able to write code using expert system rules, e.g., in KnowledgeTool, (D) present to the writer of rules and code an automatically up to date object model of the target systems, (D) via the transactional integrity, etc., have coordination among several rules and several systems much as in relational database. The most common approach to monitoring was use of thresholds on variables one at a time. Such monitoring is necessarily essentially a continually applied statistical hypothesis test with null hypothesis that the system is healthy and a detection of a problem is essentially the same as rejection of that null hypothesis. Well, to have a more powerful test, that is, better combinations of rates of false alarms and missed detections, it would be good to have the tests be multi-dimensional, that is, consider several variables jointly instead of separately and independently. So, wanted some statistical hypothesis tests that were multi-dimensional. Next, commonly in statistical hypothesis testing, know the probability distribution of the data under the null hypothesis, but there have been tests that were distribution-free, that is, that made no assumptions about probability distributions. For the work in system monitoring and management, with multi-dimensional data, distribution-free tests were essential since in practice finding the distributions of multi-dimensional data was hopeless. So, needed some statistical hypothesis tests that were both multi-dimensional and distribution-free. So, invented some. The intention was that such hypothesis tests would commonly be better means of problem detection than the usual rule left hand sides, i.e., When CPU_busy > 90% AND paging_rate > 100 AND later shipped by IBM as part of NetView system monitoring and management automation. An intention was that rules written in KnowledgeTool would run in RODM.