Consider a social media platform with hundreds of millions of online users at any time, utilizing a social graph that has many billions of nodes and edges. The problem this paper addresses is how to provide each user a continuously fresh, up-to-date view of the parts of the social graph they are currently interested in, so as to provide a positive interactive user experience. The problem is challenging because the social graph mutates at a high rate, users change their focus of interest frequently, and some mutations are of interest to many online users.

Continuous deployment is the practice of releasing software updates to production as soon as it is ready, which is receiving increased adoption in industry. The frequency of updates of mobile software has traditionally lagged the state of practice for cloud-based services for a number of reasons. Mobile versions can only be released periodically. Users can choose when and if to upgrade, which means that several different releases coexist in production. There are hundreds of Android hardware variants, which increases the risk of having errors in the software being deployed.

The functionality of many real-time systems depends critically on their software. It is important to know whether their software operates correctly or whether failures are occurring. This would help system operators take corrective actions before minor problems escalate into major disruptions. The paper considers one approach to automatic detection of software failures called supervision. In this approach, a separate unit called the supervisor observes the inputs and outputs of the target program. The supervisor knows what the intended behavior of the target program is and reports deviations as failures. The focus is on event-driven, embedded real-time software. The paper first overviews major issues involved in supervision. These include the definition of correct behavior, observability of program inputs and outputs, dealing with specification nondeterminism, tradeoffs between failure detection accuracy and computational cost, and the continuation of supervision after occurrences of failures. The paper then summarizes experience obtained in supervision of a control program of a small telephone exchange. The exchange and its telephones were simulated on a multiprocessor workstation. The summary includes the results obtained for failure detection capability and computational cost.

Software supervision is an approach to the automatic detection of software failures. A supervisor observes the inputs and outputs of a target system. It uses a model of correct behavior, derived from the target system's requirement specification. Discrepancies between specified and observed behaviors are reported as failures. Applications of the supervisor include online failure detection in real time reactive systems, fault localization and automatic collection of failure data. The paper describes a hierarchical approach to supervision. The approach differs from previous approaches in that supervision is split into two sub problems: tracking the behavior of the target system and detailed behavior checking. The architecture of the hierarchical supervisor has two layers: the path detection layer and the base supervisor layer. The hierarchical approach results in a significant reduction in computational cost arising from specification nondeterminism. The approach was evaluated by supervising the call processing software of a small telephone exchange, executed under random telephone traffic at different loads. Several thousand failures were individually seeded into the output generated by the exchange. The supervisor was able to detect the presence of all seeded failures. Reductions in computational cost of several orders of magnitude were measured in comparison with the direct, single layer supervisor.

An approach to automate detection of behavioral failures during system testing is described. A supervisor monitors the inputs and outputs of a system under test. It reports discrepancies between observed and specified behaviors as failures. Failures due to both design and implementation are detectable. The approach presented is able to tolerate legal behavioral alternatives arising out of specification non-determinism.

The focus of this paper is on an approach to the automatic failure detection of reactive software systems called specification-based supervision. Assumed is that the software is specified in a formalism based on communicating extended finite state machines (CEFSMs). The major difficulty in supervising such systems is that the supervisor must account for all possible behaviors that are permissible under the non-determinism present in the specification. An approach to the automatic detection of failures based on the theory of beliefs is presented. This theory was developed to deal with the nondeterminism present in CEFSM based formalisms. The specification language SDL, standardized by the International Telecommunication Union, is used as a concrete example. In the theory of beliefs, each behavioral alternative is represented as a separate belief of one or more specification CEFSMs. Beliefs are combined into consistent belief sets that represent legitimate external behaviors. A consistent belief set representing a behavior that does not match the actually observed behavior is terminated. If all consistent belief sets have been terminated, the observed behavior is not legitimate and is reported as a failure of the target software system. A prototype implementation of a belief-based supervisor was developed. The implementation was used to monitor execution of a small telephone exchange. Both the supervisor and exchange were emulated on a workstation. Statistics characterizing the number of consistent belief sets are presented.