Context:

Decision making by software systems that face uncertainty needs tracing to support understandability, as accountability is crucial. While logging has been essential to support explanations and understandability of behaviour, several issues still persist, such as the high cost for managing large logs, not knowing what to log, and the inability of logging techniques to relate events to each other or to specific occurrences of high-level activities in the system.

Objective:

Cronista is an alternative to logging for systems that act on top of runtime models. Instead of targeting the running systems, Cronista automatically collects the provenance of changes made to the runtime models, which aim at leveraging high-level representations, to produce more concise historical records. The provenance graphs capture causal links between those changes and the activities of the system, which are used to investigate issues.

Method:

Cronista’s architecture is described with the current design and the implementation of its high-level components for single-machine, multi-threaded systems. Cronista is applied to a traffic-simulation case study. The trade-offs of two different storage solutions are evaluated, i.e. the CDO model repositories, and JanusGraph graph databases.

Results:

Integrating Cronista into the case study requires only minor code changes. Cronista collected provenance graphs for the simulations as they ran, using both CDO and JanusGraph. Both solutions highlighted the cause of a seeded defect in the system. For the longer executions, both CDO and JanusGraph showed negligible overhead on the simulation times. Querying and visualisation tools were more user-friendly in JanusGraph than in CDO.

Conclusion:

Cronista demonstrates the feasibility of recording fine-grained provenance for the evolution of runtime models, while using it to investigate issues. User convenience and resource requirements need to be balanced. The paper present how the available technologies studied offer different trade-offs to satisfy the balance required.

中文翻译：

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Cronista：用于运行时模型的多数据库自动来源收集系统

语境：

面临不确定性的软件系统的决策需要跟踪以支持可理解性，因为问责制至关重要。虽然日志记录对于支持行为的解释和可理解性至关重要，但一些问题仍然存在，例如管理大型日志的成本高、不知道要记录什么，以及日志记录技术无法将事件相互关联或与特定事件相关联系统中的高层活动。

客观的：

Cronista是在运行时模型之上运行的系统日志记录的替代方案。Cronista不是针对正在运行的系统，而是自动收集对运行时模型所做更改的出处，旨在利用高级表示来生成更简洁的历史记录。出处图捕捉了这些变化与系统活动之间的因果关系，用于调查问题。

方法：

Cronista的架构是用当前的设计和其用于单机、多线程系统的高级组件的实现来描述的。Cronista应用于交通模拟案例研究。评估了两种不同存储解决方案的权衡，即 CDO 模型存储库和 JanusGraph 图数据库。

结果：

将Cronista集成到案例研究中只需要对代码进行少量更改。Cronista收集出处为图形模拟，因为他们跑了，同时使用CDO和JanusGraph。这两种解决方案都强调了系统中存在种子缺陷的原因。对于更长的执行时间，CDO 和 JanusGraph 的模拟时间开销都可以忽略不计。JanusGraph 中的查询和可视化工具比 CDO 中的更加用户友好。

结论：

Cronista展示了为运行时模型的演变记录细粒度来源的可行性，同时使用它来调查问题。需要平衡用户便利性和资源需求。本文介绍了所研究的可用技术如何提供不同的权衡来满足所需的平衡。