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1

A Three Dimensional Empirical Study of Logging Questions From Six Popular Q & A Websites

Gujral Harshit, Sharma Abhinav, Lal Sangeeta, Kumar Lov

e-Informatica Software Engineering Journal

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2019

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Vol. 13, nr 1

105--139

EN

Background: Q&A websites such as StackOverflow or Serverfault provide an open platform for users to ask questions and to get help from experts present worldwide. These websites not only help users by answering their questions but also act as a knowledge base. These data present on these websites can be mined to extract valuable information that can benefit the software practitioners. Software engineering research community has already understood the potential benefits of mining data from Q&A websites and several research studies have already been conducted in this area. Aim: The aim of the study presented in this paper is to perform an empirical analysis of logging questions from six popular Q&A websites. Method: We perform statistical, programming language and content analysis of logging questions. Our analysis helped us to gain insight about the logging discussion happening in six different domains of the StackExchange websites. Results: Our analysis provides insight about the logging issues of software practitioners: logging questions are pervasive in all the Q&A websites, the mean time to get accepted answer for logging questions on SU and SF websites are much higher as compared to other websites, a large number of logging question invite a great amount of discussion in the SoftwareEngineering Q&A website, most of the logging issues occur in C++ and Java, the trend for number of logging questions is increasing for Java, Python, and Javascript, whereas, it is decreasing or constant for C, C++, C#, for the ServerFault and Superuser website 'C' is the dominant programming language.

2

ECLogger: Cross-Project Catch-Block Logging Prediction Using Ensemble of Classifiers

Lal S., Sardana N., Sureka A.

e-Informatica Software Engineering Journal

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2017

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Vol. 11, nr 1

7--38

EN

Background: Software developers insert log statements in the source code to record program execution information. However, optimizing the number of log statements in the source code is challenging. Machine learning based within-project logging prediction tools, proposed in previous studies, may not be suitable for new or small software projects. For such software projects, we can use cross-project logging prediction. Aim: The aim of the study presented here is to investigate cross-project logging prediction methods and techniques. Method: The proposed method is ECLogger, which is a novel, ensemble-based, cross-project, catch-block logging prediction model. In the research We use 9 base classifiers were used and combined using ensemble techniques. The performance of ECLogger was evaluated on on three open-source Java projects: Tomcat, CloudStack and Hadoop. Results: ECLoggerBagging, ECLoggerAverageVote, and ECLoggerMajorityVote show a considerable improvement in the average Logged F-measure (LF) on 3, 5, and 4 source!target project pairs, respectively, compared to the baseline classifiers. ECLoggerAverageVote performs best and shows improvements of 3.12% (average LF) and 6.08% (average ACC – Accuracy). Conclusion: The classifier based on ensemble techniques, such as bagging, average vote, and majority vote outperforms the baseline classifier. Overall, the ECLoggerAverageVote model performs best. The results show that the CloudStack project is more generalizable than the other projects.

3

Tracing multiple mobile objects by a network of intelligent detectors

Górska M.

Logistyka

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2011

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nr 3

EN

We study concepts for tracing moving objects in a certain domain by means of a set of checkpoints (observers) located at chosen stationary points within the domain. The observers are assumed to recognize objects of interest when appearing in their vicinity. Information about sighted objects is transmitted in real time to a central server (Operation Center). Conversely, updated watch lists are transferred back to the observers. As proof of concept, we shall simulate the action of a synthetic net on some arbitrarily chosen domain.

PL

Rozważana jest koncepcja śledzenia ruchu obiektów po pewnym ustalonym obszarze za pomocą zbioru punktów kontrolnych (obserwatorów) umiejscowionych w jego wnętrzu. Założono, że każdy z obserwatorów jest w stanie rozpoznać obiekty poszukiwane, w przypadku, gdy pojawiają się one w jego otoczeniu. Informacja o takim zdarzeniu jest przekazana w czasie rzeczywistym do centralnego serwera (centrum zarządzania). W przeciwną stronę serwer przesyła uaktualnienia list poszukiwanych obiektów do jednostek obserwacyjnych. Koncepcję sprawdzono drogą symulacji komputerowej, na podstawie danych losowych.

4

Aspekty technologiczne wdrażania zharmonizowanego systemu informacji rzecznej

Stateczny A.

Logistyka

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2011

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nr 6

PL

W artykule przedstawiono analizę techniczną usług i technologii RIS w aspekcie wdrożenia systemu na dolnej Odrze. Omówiono wszystkie cztery kluczowe technologie RIS: ECDIS śródlądowy, komunikaty dla kierowników statków, elektroniczne raportowanie statków oraz system kontroli ruchu statków wskazując ich wzajemne powiązania.

EN

In this article the technical analyze of RIS services and technology on the lower Odra river RIS implementation aspect was presented. All four key technologies: Inland ECDIS, Notice to Skippers (NtS), Vessel Tracking and Tracing (VTT) and Electronic Reporting International (ERI) were described with focus on their interaction.