Analysing problem handling schemes in software projects

Sosnowski, J.; Dobrzyński, Bartosz; Janczarek, Paweł

doi:10.1016/j.infsof.2017.06.006

Cited by 11 publications

(22 citation statements)

References 15 publications

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“…In many papers testing is correlated with software reliability. Software reliability growth models (SRGMs) are proposed to predict bugs in software, needed testing time to achieve an assumed quality level (release time), optimization of resources and test costs ( [7] [11] and references therein). On the other hand, diverse publications focus on specific test problems: test algorithms based on structural, functional, and mixed approaches, test efficiency, software quality, etc.…”

Section: Background and Related Workmentioning

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%

“…We consider test reports, event and performance logs, software issue and version control repositories. In the literature these repositories were analyzed separately and targeted at specific aspects, e.g., software reliability, software production improvement [7] [8]. They were not correlated explicitly with test processes.…”

Section: Introductionmentioning

confidence: 99%

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Extending the Space of Software Test Monitoring: Practical Experience

Lasynskyi

Sosnowski

2021

IEEE Access

Self Cite

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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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Section: Background and Related Workmentioning

confidence: 99%

Section: B Test Assessmentmentioning

confidence: 99%

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Extending the Space of Software Test Monitoring: Practical Experience

Lasynskyi

Sosnowski

2021

IEEE Access

Self Cite

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“…This smart lighting system with open API integrates seamlessly with the IT system and enables a variety of software applications to create a more intelligent work environment for both building operations managers and employees. In literature, the use of software development schemes and repositories are well described [32][33][34]. It is demonstrated that detailed problem handling reports will extend the space and quality of statistical analysis for software [34].…”

Section: Case 2: Industrial Datamentioning

confidence: 99%

“…In literature, the use of software development schemes and repositories are well described [32][33][34]. It is demonstrated that detailed problem handling reports will extend the space and quality of statistical analysis for software [34]. It is without doubts that detailed reports will provide significant improvement of software development processes as well as better reliability predictions [32].…”

Section: Case 2: Industrial Datamentioning

confidence: 99%

Software Reliability for Agile Testing

Driel

Bikker²,

Tijink³

et al. 2020

Mathematics

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It is known that quantitative measures for the reliability of software systems can be derived from software reliability models, and, as such, support the product development process. Over the past four decades, research activities in this area have been performed. As a result, many software reliability models have been proposed. It was shown that, once these models reach a certain level of convergence, it can enable the developer to release the software and stop software testing accordingly. Criteria to determine the optimal testing time include the number of remaining errors, failure rate, reliability requirements, or total system cost. In this paper, we present our results in predicting the reliability of software for agile testing environments. We seek to model this way of working by extending the Jelinski–Moranda model to a “stack” of feature-specific models, assuming that the bugs are labeled with the features they belong to. In order to demonstrate the extended model, two use cases are presented. The questions to be answered in these two cases are: how many software bugs remain in the software and should one decide to stop testing the software?

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Mobile Application Testing and Assessment

Jeleński¹,

Sosnowski

2020

Theory and Applications of Dependable Computer Systems

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Analysing problem handling schemes in software projects

Cited by 11 publications

References 15 publications

Extending the Space of Software Test Monitoring: Practical Experience

Extending the Space of Software Test Monitoring: Practical Experience

Software Reliability for Agile Testing

Mobile Application Testing and Assessment

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