Evaluating Web Software Reliability Based on Workload and Failure

Data Extracted FromServer Logs

CSI518 – Group 1

By Zumrut Akcam, Kim Gero, Allen Chestoski,Javian Li and Rohan Warkad

Definition of Reliability

The increasing usage of Web software systems and attraction of society to the Web makes reliability of Web systems more important.

What is reliability for Web applications? The reliability for Web applications can be

defined as the probability of failure-free Web operation completions.[1]

Failure is “the event of a system deviating from its specified behavior like obtaining or delivering information”.[2]

Failure Sources

Failures are caused from the following sources: Host, network or browser failures: computer

systems, network or software failures, etc. Source content failures: missing, inaccessible

files, JavaScript errors, etc. User errors: improper usage, mistyped URLs.[1]

Project Goal

This project concentrates on the minimizing of source content failures to strengthen the reliability of Web applications.

With this project, we try to accomplish the following goals as a team:

Attempt to extend work on testing the reliability of websites.

Gain experience doing a research project

Workload Analysis

To analyze the reliability of web systems, we're going to use the access logs and error logs under the title of server logs.

Failure information alone is not enough for assessing the reliability of a system so measuring the workload is also necessary.

The measurements for workload are byte count, user count, session count and number of hits.

Workload Measures Hit Count: Each hit shows the specific request

to a web server. Misleading because individual hits show high variability.

Byte Count: Number of bytes transferred gives finer granularity than hit count.

User Count: Treat each client IP address as one user. Disadvantages: coarse granularity.

Session Count: Number of user sessions can be calculated by IP address and access times using time limits per user[3].

Sprint 1 Goals Read relevant research papers Identify factors that may effect reliability analysis Determine a system to analyze reliability on Identify a metric to analyze reliability Gather access and error logs

Relevant research papers Toan Huynh and James Miller. 2009. Another viewpoint on

"evaluating web software reliability based on workload and failure data extracted from server logs". Empirical Softw. Engg. 14, 4 (August 2009), 371-396. DOI=10.1007/s10664-008-9084-6 http://dx.doi.org/10.1007/s10664-008-9084-6

Jeff Tian, Sunita Rudraraju, and Zhao Li. 2004. Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs. IEEE Trans. Softw. Eng. 30, 11 (November 2004), 754-769. DOI=10.1109/TSE.2004.87 http://dx.doi.org/10.1109/TSE.2004.87

We hope to extend work on these papers

Factors that may effect reliability analysis Byte count User count Session count Error count

System to analyze reliability on Reliability analysis via error logs Variety of reliability requirements Commercial and non-commercial We will try to record the technologies the

websites employ (Apache, DNN, ISS, PHP, ColdFusion, etc..)

The Nelson Method R = (n-f)/n = 1 – (f/n) = 1 – r R: Reliability f: Total number of failures n: Number of workload units r: Failure rate

Mean Time Between Failures (MTBF) MTBF = (1/f) Σi ti

MTBF = n/f

Identify a metric to analyze reliability

Access and error logs Universities and companies refusing to provide

us with access and error logs. Confidentiality reasons Outsourcing server management to external

companies

Sprint 2 Goals Collect enough log files for calculation Automate processes to extra data (user, session, byte, and error counts) and convert them into excel format Log Parser

Sprint 2 Progress A web developer agreed to send all logs he has (ASP.NET / DNN)

What is DotNetNuke (DNN)

Founded 2006 .NET version of Drupal An open source platform for building web sites and web applications based on Microsoft .NET technology. Leading open source ASP.NET web content management system and .NET development framework ~100 employees Has been downloaded over 6 million times 5th Version

Our DNN Logs 10 Websites Window Server (Same Server) SQL Server 2008~1000 unique visiters per dayLogs contain

User count Little Error count

Doesn't contain Session count Byte count

Sprint 2 Problems Still looking for logs and may have to consider generating our information To create our own logs is under discussion

LogParser

Microsoft tool designed for parsing text-based logs

Flexible Support for common log file formats SQL style queries allow for targeted data extraction

Can output to .csv Ease of bulk parsing

Operates off Windows command prompt

Unique Client-IP’s for One Log Set

Sprint 3 and Beyond

Information Extraction

Plot graphs and charts on parsed data Mine the data and derive relations Reliability models

Why Nelson Model? Calculate Operational Reliability

R = (n-f)/n = 1-r MTBF = (1/f)Σti

Conclusion

Derive key factors affecting reliability Provide Inputs

Validating previous research Pointers for topics to explore for future research Detailed documentation and publishing

References

[1] J.Tian, S.Rudraraju, Z.Li, “Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs”,2004.

[2] T.Huynh, J.Miller, “Another viewpoint on 'Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs'”,2008.

[3] G. Albeanu, A. Averian, I. Duda, “Web Software Reliability Engineering”,2009.