Software failures are still a major concern in mission- and enterprise-critical contexts, despite significant efforts spent in software testing. In fact, while software testing is effective against easily-reproducible bugs (Bohrbugs), it is considerably less suitable for dealing with bugs that lead to hard-to-reproduce failures (Mandelbugs). On the positive side, the elusive nature of Mandelbugs provides opportunities for failure recovery, which are investigated in this paper. Based on real cases of Mandelbugs in eleven Information Technology (IT) systems running in production, the paper proposes a model that describes the recovery processes in IT systems. It then presents closed-form expressions, and a numerical analysis, of the mean time to recovery, and the software (un)availability. This analysis allows the designer to compare recovery strategies, as well as to determine the parameters having a high influence on the efficacy of recovery from failures caused by Mandelbugs.

Several studies have been carried out on software bugs analysis and classification for life and mission critical systems, which include reproducible bugs called Bohrbugs, and hard to reproduce bugs called Mandelbugs. Although software reliability in IT systems has been studied for years, there are only a few formal analytic models for recovery from Mandelbugs. This paper discusses in detail several real cases of Mandelbugs and presents a simple flowchart which describes the recovery processes implemented in IT systems for a large variety of Mandelbugs. The flowchart is based on more than 10 IT systems that are running in production. The paper then presents a closed-form expression of the mean time to recovery from these bugs. Measures of interest including mean time to recovery and system unavailability are computed. A numerical and parametric sensitivity analysis of the model parameters are carried out. This analysis allows the designer to find out important parameter(s) for the recovery from failures due to Mandelbugs.

Performance engineering is a badly needed skill for implementing and running IT systems, but performance engineers are hard to find in the market. This paper presents our experiences in rolling out training and certification in a first level course on performance engineering across a large enterprise. We present data and lessons learned on the nominations for the rollout, the design and analysis of theory and practical exams, and the methods used to ensure fairness in a rollout spanning hundreds of nominations. We present results that show trainees to perform exceeding well much against conventional wisdom, and we also show how the success of the rollout has led to a number of beneficial initiatives for the company.

The performance potential of run-to-completion (RTC) parallel processor scheduling policies is investigated by examining whether (1) application execution rate characteristics such as average parallelism (avg) and processor working set (PWS) and/or (2) limited preemption can be used to improve the performance of these policies. We address the first question by comparing policies (previous as well as new) that differ only in whether or not they use execution rate characteristics and by examining a wider range of the workload parameter space than previous studies. We address the second question by comparing a simple two-level queueing policy with RTC scheduling in the second level queue against RTC policies that don't allow any preemption and against dynamic equiallocation(EQ).