Robert E. Mullen

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This paper explores a novel application of queuing theory to the corrective software maintenance problem to support quantitative balancing between resources and responsiveness. Initially, we provide a detailed description of the states a defect traverses from find to fix and a definition and justification of mean time to resolution as a useful process(More)
An understanding of the distribution of software failure rates and its origin will strengthen the relation of software reliability engineering both to other aspects of software engineering and to the wider field of reliability engineering. The present paper proposes that the distribution of failure rates for faults in software systems tends to be lognormal.(More)
Corrective software maintenance, which consists of fixing defects that escape detection and manifest as field failures, is expensive, yet vital to ensuring customer satisfaction. To allocate and use maintenance resources effectively, it is necessary to understand the defect occurrence phenomenon in the field. A preliminary analysis of the defect occurrence(More)
We hypothesize that software defect repair times can be characterized by the Laplace Transform of the Lognormal (LTLN) distribution. This hypothesis is rooted in the observation that software defect repair times are influenced by the multiplicative interplay of several factors, and the lognormal distribution is a natural choice to model rates of occurrence(More)
When testing software, both effort and delay costs are related to the number of tests developed and executed. However the benefits of testing are related to coverage achieved and defects discovered. We establish a novel relationship between test costs and the benefits, specifically between the quantity of testing and test coverage, based on the Lognormal(More)
This paper presents an empirical comparison of the growth characteristics of four code coverage measures, block, decision, c-use and p-use, as testing is increased. Due to the theoretical foundations underlying the lognormal software reliability growth model, we hypothesize that the growth for each coverage measure is lognormal. Further, since for a given(More)
The logical interrelationship between different code coverage types has been well studied, but less so their evolution through time or test. We study the dynamic relationship of four coverage types, namely, block, decision, c-use and p-use by comparing their growth using empirical coverage data generated from extensive testing of a software application with(More)
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