Michael Grottke

The fundamentals of software aging

Since the notion of software aging was introduced thirteen years ago, the interest in this phenomenon has been increasing from both academia and industry. The majority of the research efforts in studying software aging have focused on understanding its effects theoretically and empirically. However, conceptual aspects related to the foundation of this phenomenon have not been covered in the literature. This paper discusses foundational aspects of the software aging phenomenon, introducing new concepts and interconnecting them with the current body of knowledge, in order to compose a base taxonomy for the software aging research. Three real case studies are presented with the purpose of exemplifying many of the concepts discussed.

An empirical investigation of fault types in space mission system software

As space mission software becomes more complex, the ability to effectively deal with faults is increasingly important. The strategies that can be employed for fighting a software bug depend on its fault type. Bohrbugs are easily isolated and removed during software testing. Mandelbugs appear to behave chaotically. While it is more difficult to detect these faults during testing, it may not be necessary to correct them; a simple retry after a failure occurrence may work. Aging-related bugs, a sub-class of Mandelbugs, can cause an increasing failure rate. For these faults, proactive techniques may prevent future failures. In this paper, we analyze the faults discovered in the on-board software for 18 JPL/NASA space missions. We present the proportions of the various fault types and study how they have evolved over time. Moreover, we examine whether or not the fault type and attributes such as the failure effect are independent.

Performance Assurance via Software Rejuvenation: Monitoring, Statistics and Algorithms

We present three algorithms for detecting the need for software rejuvenation by monitoring the changing values of a customer-affecting performance metric, such as response time. Applying these algorithms can improve the values of this customer-affecting metric by triggering rejuvenation before performance degradation becomes severe. The algorithms differ in the way they gather and use sample values to arrive at a rejuvenation decision. Their effectiveness is evaluated for different sets of control parameters, including sample size, using simulation. The results show that applying the algorithms with suitable choices of control parameters can significantly improve system performance as measured by the response time

Fault triggers in open-source software: An experience report

With software systems becoming increasingly large and complex, many difficulties in coping with software bugs arise for developers. Despite good development practices, thorough testing, and proper maintenance policies, a non-negligible number of bugs remain in the released software. Understanding the type of residual bugs is fundamental for adopting proper countermeasures in current and future software releases. Depending on the fault triggering conditions that lead to a failure, developers can introduce fault-tolerance mechanisms and plan verification and validation strategies. In this paper, we analyze bugs in four large open-source software systems during their lifecycle, based on the concept of fault triggers. We first investigate how the type of system affects the bug type proportions, and their evolution over years. Then, an analysis of bug subtypes is performed, so as to better understand their nature, followed by a comparison with respect to attributes such as their average time to fix and severity.

Achieving and assuring high availability

We discuss availability aspects of large software- based systems. We classify faults into Bohrbugs, Mandelbugs and aging-related bugs, then examine mitigation methods for the last two bug types. We also consider quantitative approaches to availability assurance.

Ten fallacies of availability and reliability analysis

As modern society becomes more and more dependent on computers and computer networks, vulnerability and downtime of these systems will significantly impact daily life from both social and economic point of view. Words like reliability and downtime are frequently heard on radio and television and read in newspapers and magazines. Thus reliability and availability have become popular terms. However, even professionals are in the danger of misunderstanding these basic concepts. Such misunderstandings can hinder advances in designing and deploying high-availability and high-reliability systems. This paper delves into ten fallacious yet popular notions in availability and reliability. While the discussions on the first five fallacies clarify some misconceptions among reliability engineers working on modeling and analysis, the remaining five fallacies provide important insights to system engineers and companies focusing on system level integration.

On a method for mending time to failure distributions

Many software reliability growth models assume that the time to next failure may be infinite; i.e., there is a chance that no failure will occur at all. For most software products this is too good to be true even after the testing phase. Moreover, if a non-zero probability is assigned to an infinite time to failure, metrics like the mean time to failure do not exist. In this paper, we try to answer several questions: Under what condition does a model permit an infinite time to next failure? Why do all non-homogeneous Poisson process (NHPP) models of the finite failures category share this property? And is there any transformation mending the time to failure distributions? Indeed, such a transformation exists; it leads to a new family of NHPP models. We also show how the distribution function of the time to first failure can be used for unifying finite failures and infinite failures NHPP models.

Recovery from Failures Due to Mandelbugs in IT Systems

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.

Variational Bayesian Approach for Interval Estimation of NHPP-Based Software Reliability Models

In this paper, we present a variational Bayesian (VB) approach to computing the interval estimates for nonhomogeneous Poisson process (NHPP) software reliability models. This approach is an approximate method that can produce analytically tractable posterior distributions. We present simple iterative algorithms to compute the approximate posterior distributions for the parameters of the gamma-type NHPP-based software reliability model using either individual failure time data or grouped data. In numerical examples, the accuracy of this VB approach is compared with the interval estimates based on conventional Bayesian approaches, i.e., Laplace approximation, Markov chain Monte Carlo (MCMC) method, and numerical integration. The proposed VB approach provides almost the same accuracy as MCMC, while its computational burden is much lower.

Response Time Distributions in Networks of Queues

This chapter addresses the issue of determining the response time distribution in networks of queues. Four different techniques are described and demonstrated. A two step numerical approach to compute the response time distribution for closed Markovian networks with general connectivity, a technique for determining the approximate (exact under certain conditions) response time distribution of a defined subset of open M/M/c/b Markovian networks using predefined continuous timeMarkov chain (CTMC) “response time blocks,” an expansion of “response time blocks” to openMarkovian networks with general phase type (PH) service time distributions, and an approach for handling non Markovian networks having M/G/1 priority and PH/G/1 queues. These techniques are shown to give accurate results with much smaller CTMCs or semi Markov processes than exact analysis.