Discovering specification violations in networked software systems

Walls, Robert J.; Bruii, Yuriy; Liberatore, Marc; Levine, Brian Neil

doi:10.1109/issre.2015.7381842

Cited by 9 publications

(7 citation statements)

References 36 publications

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“…Execution traces can be defined as an ordered list of events that have occurred during the program execution. Event is a general term that can refer to a function call [3], raised exception, network packet [14], [15], keyboard or mouse events, and more. Events can be collected in different ways, for instance, from operating systems [10], framework [16], or programmers' logs [17].…”

Section: Background and Related Workmentioning

confidence: 99%

An Empirical Study on Practicality of Specification Mining Algorithms on a Real-World Application

Mashhadi

Hemmati

2019

2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)

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Dynamic model inference techniques have been the center of many research projects recently. There are now multiple open source implementations of state-of-the-art algorithms, which provide basic abstraction and merging capabilities. Most of these tools and algorithms have been developed with one particular application in mind, which is program comprehension. The output models can abstract away the details of the program and represent the software behaviour in a concise and easy to understand form. However, one application context that is less studied is using such inferred models for debugging, where the behaviour to abstract is a faulty behaviour (e.g., a set of execution traces including a failed test case). We tried to apply some of the existing model inference techniques in a real-world industrial context to support program comprehension for debugging. Our initial experiments have shown many limitations both in terms of implementation as well as the algorithms. The paper will discuss the root cause of the failures and proposes ideas for future improvement.

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Section: Background and Related Workmentioning

confidence: 99%

An Empirical Study on Practicality of Specification Mining Algorithms on a Real-World Application

Mashhadi

Hemmati

2019

2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)

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“…The approach completely overlooks the impact of the wireless network service. In another work , networked software systems are checked for violations in functional specifications using fuzz testing and model refinement. For the Android platform, a model‐based test generation tool is provided to test mobile applications .…”

Section: Literature Reviewmentioning

confidence: 99%

An end‐user‐centric test generation methodology for performance evaluation of mobile networked applications

Al‐tekreeti

Abdrabou

Naik

2019

Software Testing Verif & Rel

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We propose a model-based test generation methodology to evaluate the impact of the interaction of the wireless network and application configurations on the performance of mobile networked applications. We consider waiting time delay to model wireless network quality. We classify mobile applications into two groups. Group I represents applications where end-user experience is mainly affected by waiting time delay during service consumption, while group II represents applications where end-user experience is affected by waiting time delay before service consumption. Test generation is formulated as an inversion problem. However, for group I applications, solving the inversion problem is expensive. Therefore, we utilize metamorphic testing to mitigate the cost of test oracles. We formulate metamorphic test generation as maximization of the distance between seed and follow-up test cases. Two test coverage criteria are proposed: user experience and user-experience-and-input interaction. Network models are developed for a mobile device that has network access through a WiFi hot spot and uses either transmission control protocol or user datagram protocol. Two mobile applications are used to demonstrate the methodology: multimedia streaming and web browsing. Application of the methodology when user actions are taken into consideration is also addressed. The effectiveness of the methodology is evaluated using two metrics: the incurred time cost and redundancy in the generated test suite. The obtained results show the advantage of casting test generation as an inversion problem, compared with random testing. For apps with intensive performance models, combining metamorphic testing with the methodology has tremendously reduced the cost of test oracles. 15 of 38 state y. Therefore, the SUT desired behaviour introduces the following two constraints (Procedure 3.S1), where B, M , and L are defined as an integer number of multimedia frames:M Ä B and L Ä M 1:(4) 4.1.2. The wireless network model. The end user is streaming via a WiFi hot spot and using the UDP. We assume all the fluctuations in the wireless link and the queuing effects of the different routers along the path from the server to the client device manifest as a time delay. That is, packet loss is negligible. A reusable network model for the UDP scenario was developed in our previous work [15]. We have developed two analytical expressions for the mean and variance of packet interarrival time delay. The probability distribution was matched with the hyper-Erlang distribution. The network impact is captured by three operating parameters (NOPs): the data rate (D), the mean rate of frame arrivals into the access point ( ) per user, and the number of end users (N ) connected to the AP. The data rate according to the IEEE 802.11 a/g standard can be in one of the following values: 6, 9, 12, 18, 24, 32, 48, or 54 Mbps. It mainly relates to the quality of the wireless connection between the AP and the end user. Regarding the number of users N , the network model is validated...

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“…Other work mines a variety of distributed system information for SE purposes. For example, some work uses mining to detect dependencies [37], anomalies [53,55], and performance bugs [48].…”

Section: Related Workmentioning

confidence: 99%

Inferring and asserting distributed system invariants

Grant

Cech

Beschastnikh

2018

Proceedings of the 40th International Conference on Software Engineering

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Distributed systems are difficult to debug and understand. A key reason for this is distributed state, which is not easily accessible and must be pieced together from the states of the individual nodes in the system.We propose Dinv, an automatic approach to help developers of distributed systems uncover the runtime distributed state properties of their systems. Dinv uses static and dynamic program analyses to infer relations between variables at different nodes. For example, in a leader election algorithm, Dinv can relate the variable leader at different nodes to derive the invariant ∀ nodes i, j, leader i = leader j . This can increase the developer's confidence in the correctness of their system. The developer can also use Dinv to convert an inferred invariant into a distributed runtime assertion on distributed state.We applied Dinv to several popular distributed systems, such as etcd Raft, Hashicorp Serf, and Taipei-Torrent, which have between 1.7K and 144K LOC and are widely used. Dinv derived useful invariants for these systems, including invariants that capture the correctness of distributed routing strategies, leadership, and key hash distribution. We also used Dinv to assert correctness of the inferred etcd Raft invariants at runtime, using these asserts to detect injected silent bugs.

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Discovering specification violations in networked software systems

Cited by 9 publications

References 36 publications

An Empirical Study on Practicality of Specification Mining Algorithms on a Real-World Application

An Empirical Study on Practicality of Specification Mining Algorithms on a Real-World Application

An end‐user‐centric test generation methodology for performance evaluation of mobile networked applications

Inferring and asserting distributed system invariants

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