High-availability of software systems requires automated handling of crashes in presence of errors. Failure-oblivious computing is one technique that aims to achieve high availability. We note that failure-obliviousness has not been studied in depth yet, and there is very few study that helps understand why failure-oblivious techniques work. In order to make failure-oblivious computing to have an impact in practice, we need to deeply understand failure-oblivious behaviors in software. In this paper, we study, design and perform an experiment that analyzes the size and the diversity of the failure-oblivious behaviors. Our experiment consists of exhaustively computing the search space of 16 field failures of large-scale open-source Java software. The outcome of this experiment is a much better understanding of what really happens when failure-oblivious computing is used, and this opens new promising research directions.
Rx @cite_8 is a runtime repair system based on changing the environment upon failures. Rx employs checkpoint-and-rollback for re-executing the buggy code when failures happen. The differences are as follows: 1) Rx does not change the execution itself but the environment 2) the search space of Rx is smaller (a set of predefined strategies) 3) Rx’ experiment does not include systematic exploration of the search space.
@cite_8
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Many applications demand availability. Unfortunately, software failures greatly reduce system availability. Prior work on surviving software failures suffers from one or more of the following limitations: Required application restructuring, inability to address deterministic software bugs, unsafe speculation on program execution, and long recovery time.This paper proposes an innovative safe technique, called Rx, which can quickly recover programs from many types of software bugs, both deterministic and non-deterministic. Our idea, inspired from allergy treatment in real life, is to rollback the program to a recent checkpoint upon a software failure, and then to re-execute the program in a modified environment. We base this idea on the observation that many bugs are correlated with the execution environment, and therefore can be avoided by removing the "allergen" from the environment. Rx requires few to no modifications to applications and provides programmers with additional feedback for bug diagnosis.We have implemented RX on Linux. Our experiments with four server applications that contain six bugs of various types show that RX can survive all the six software failures and provide transparent fast recovery within 0.017-0.16 seconds, 21-53 times faster than the whole program restart approach for all but one case (CVS). In contrast, the two tested alternatives, a whole program restart approach and a simple rollback and re-execution without environmental changes, cannot successfully recover the three servers (Squid, Apache, and CVS) that contain deterministic bugs, and have only a 40 recovery rate for the server (MySQL) that contains a non-deterministic concurrency bug. Additionally, RX's checkpointing system is lightweight, imposing small time and space overheads.