Holistic Processing and Exploring Event Logs

Kubacki, Marcin; Sosnowski, J.

doi:10.1007/978-3-319-65948-0_12

Cited by 8 publications

(10 citation statements)

References 19 publications

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“…The text in related logs was based on dictionary of several thousand of unique words. We observed these features also in logs of other projects [30].…”

Section: A General Text Miningsupporting

confidence: 64%

“…This can be supported with some quality metrics and classification methods [28] [29]. Logs record events useful in detecting and diagnosing anomalies [9] [30]. For this purpose, log parsing algorithms and tools have been developed [31] [32].…”

Section: A Test Challengesmentioning

confidence: 99%

“…This additionally confirms negligence of the pointed problems in correlation with testing, which we found as important practical issues needing investigation. [2, 5, 8, 12 -14, 34-36, 44] Testing project performance [16,17] Bug classification [17, 24-26, 28, 29] Test quality assessment [1 -4, 6, 10, 11, 15, 21, 34-37] Fault localization and program diagnosability [3,22,23,38,39] Test optimization and prioritization [18 -23, 42, 43] Logging schemes [9,28,30] Log analysis and parsing [9, 30 -32] Anomaly detection [9,33,34] Log statement optimization [9,34] Issue and version control tracking [7,25,30,37] Bug triaging [27] The created test scenarios are upgraded during the development and maintenance of the program. Moreover, in a large extent they are used during regression testing in relevance to function upgrades, extensions, or corrections.…”

Section: B Test Assessmentmentioning

confidence: 99%

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Extending the Space of Software Test Monitoring: Practical Experience

Lasynskyi

Sosnowski

2021

IEEE Access

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Software reliability depends on the performed tests. Bug detection and diagnosis are based on test outcome (oracle) analysis. Most practical test reports do not provide sufficient information for localizing and correcting bugs. We have found the need to extend the space of test result observation in data and time perspectives. This resulted in tracing supplementary test result features in event logs. They are explored with combined text mining and log parsing techniques. Another important point is correlating test life cycle with project development history journaled in issue tracking and software version control repositories. Dealing with the outlined problems, neglected in the literature, we have introduced original analysis schemes. They focus on assessing test coverage, reasons of low diagnosability, and test result profiles. Multidimensional investigation of test features and their management is supported with the developed test infrastructure. This assures a holistic insight into the test efficiency to identify test scheme deficiencies (e.g., functional inadequacy, aging, insufficient coverage) and possible improvements (test set updates). Our studies have been verified in relevance to a real commercial project (industrial case study) and confronted with the experience of testers engaged in other projects.INDEX TERMS bug diagnostics, software defect repository, software testing, testing framework, test monitoring.

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“…The text in related logs was based on dictionary of several thousand of unique words. We observed these features also in logs of other projects [30].…”

Section: A General Text Miningsupporting

confidence: 64%

Section: A Test Challengesmentioning

confidence: 99%

Section: B Test Assessmentmentioning

confidence: 99%

See 1 more Smart Citation

Extending the Space of Software Test Monitoring: Practical Experience

Lasynskyi

Sosnowski

2021

IEEE Access

Self Cite

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“…A multichannel signal decomposition approach is presented in [19] and illustrated in the analysis of real-life EEG and vibration signals. Event log analyses are mostly targeted at classification problems and detection of anomalous situations, e.g., the appearance of suspicious events or their sequences ( [7,20] and references therein), grouping logs into event sequences (workflows) and log reduction (compression) [21]. This is supported with log parsing algorithms [6,22].…”

Section: Problem Statement and Related Workmentioning

confidence: 99%

“…Time scale-dependent correlations and decomposition of TS are considered in [27]. Event log correlation is focused on finding co-occurrences of different types of events or alert reports [20,28]. In [24], faults are identified by a sequence of events, based only on their temporal arrival pattern.…”

Section: Problem Statement and Related Workmentioning

confidence: 99%

Correlating Time Series Signals and Event Logs in Embedded Systems

Krosman

Sosnowski

2021

Sensors

Self Cite

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In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in a background of noise, and sporadic event logs. The correlation process must take into account clock inconsistencies between the data acquisition and monitored devices, which provide time series signals and event logs, respectively. The idea of the presented solution is to classify event logs based on the introduced similarity metric and deriving their distribution in time. The identified event log sequences are matched with time intervals corresponding to specified sample patterns (objects) in the registered signal time series. The matching (correlation) process involves iterative time offset adjustment. The paper presents original algorithms to investigate correlation problems using the object-oriented data models corresponding to two monitoring sources. The effectiveness of this approach has been verified in power consumption analysis using real data collected from the developed Holter device. It is quite universal and can be easily adapted to other device optimisation problems.

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Log Based Analysis of Software Application Operation

Obrębski

Sosnowski

2019

Advances in Intelligent Systems and Computing

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Holistic Processing and Exploring Event Logs

Cited by 8 publications

References 19 publications

Extending the Space of Software Test Monitoring: Practical Experience

Extending the Space of Software Test Monitoring: Practical Experience

Correlating Time Series Signals and Event Logs in Embedded Systems

Log Based Analysis of Software Application Operation

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