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Modern software systems are complex and comprise many interacting and dependent components. Frequent upgrades are required to fix bugs, patch security vulnerabilities, and add or remove features. Unfortunately, many upgrades either fail or produce undesired behavior resulting in service disruption, user dissatisfaction, and/or monetary loss. To make matters worse, when upgrades fail or misbehave, developers are given limited (and often unstructured) information to pinpoint and correct the problems. In this dissertation, we propose two systems to improve the management of software upgrades. Both systems rely on environment information and dynamic execution data collected from users who have previously upgraded the software. The first (called Mojave) is an upgrade recommendation system that informs a user who intends to upgrade the software about whether the upgrade is likely to succeed. Regardless of Mojave's recommendation, if the user decides to upgrade and it fails, our second system (called Sahara) comes into play. Sahara is a failed upgrade debugging system that identifies a small subset of routines that are likely to contain the root cause of the failure. We evaluate both systems using several real upgrade failures with widely used software. Our results demonstrate that our systems are very accurate in predicting upgrade failures and identifying the likely culprits for upgrade failures. |
