We address issues related to the definition of faults, errors and failures and their separability, and attribution to the different development processes of computing systems. In particular, we deal with historical databases, which presumably contain certain data (i.e., test failure data) and describe the methodology that can be used to analyze the database and obtain the pertinent information. The validation method may be of particular importance, especially when information from the database needs to be extrapolated for a purpose other than the one for which the database was developed. Our methodology was used to evaluate the historical data collected during the development of the IBM 4381 and 9370 family of computers, and to extrapolate the faults found during the function testing.

In this paper, we report the findings of an investigation undertaken at IBM to determine whether or not existing software metrics are applicable to the microcode of large computer systems. As part of this investigation, we calculated several metrics from the microcode developed for the IBM 4381 and IBM 9370 computer systems, and used them as predictive parameters for a number of existing error prediction models. The microcode used in this case study exceeds 1.2 million lines of code written in 12 languages and comprises the microcode for the IBM ES/4381 and IBM ES/9370 computer systems. Our results suggest that only a few of the existing metrics are linearly independent, and that none of the metrics examined can be used in a regression model as a reliable error predictor.

In this paper we report on an empirical study conducted to determine whether existing software reliability models can be used to predict the errors incurred during the design, development and testing phases of the microcode of computer systems. A number of reliability models are reviewed and employed to predict the faults of the microcode development of the IBM 4381 and the IBM 9370 families of computer systems. Through the study of historical defect data from these two systems, we establish an empirical basis for the usefulness of such models in terms of accuracy in the prediction of the expected errors during the development of the microcode of computer systems.

The collection of data necessary to compute various software metrics constitutes a difficult task, especially for large projects written in multiple languages. We discus a number of issues associated with the collection of data for large commercial computer products and show that significant discrepancies in the value of some metrics may arise depending on the measurement method used. Using data collected from 4,635 microcode modules, which total s> 1.2 million lines of code and comprise the entire microcode of the IBM ES/4381 and IBM ES/9370 computer systems, we show the impact the computing methodology has on some studies associated with program metrics.

Describes a question-answering system based on fuzzy logic. The proposed system provides the capability to assess whether a database contains information pertinent to a subject of interest by evaluating each comment in the database via a fuzzy evaluator that attributes a fuzzy membership value indicating its relationship to the subject. An assessment is provided for the database as a whole regarding its pertinence to the subject of interest, and consequently comments that are considered irrelevant to the subject may be discarded. The system has been developed for the examination of databases that were created during the development of the IBM 4381 computer systems, for bookkeeping purposes, to assess whether such databases contain information pertinent to the functional changes that occurred during the development cycle. The system, however, can be applied with minimal changes to a variety of circumstances, provided that the fundamental assumptions for the development of the membership functions are respected in the new application. Its applicability, without modifications, assuming the same subject of interest, is granted for databases comprising similar characteristics to that of the original database for which the system has been developed.>