Evaluating Web Software Reliability By Zumrut Akcam, Kim Gero, Allen Chestoski, Javian Li & Rohan...
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Transcript of Evaluating Web Software Reliability By Zumrut Akcam, Kim Gero, Allen Chestoski, Javian Li & Rohan...
Evaluating Web Evaluating Web Software ReliabilitySoftware Reliability
By Zumrut Akcam, Kim Gero, Allen Chestoski,Javian Li & Rohan Warkad
CSI518 – Group 1CSI518 – Group 1
Agile DevelopmentAgile Development
The Agile Development ProcessThe Agile Development Process
How does Agile work?
How did our class use Agile?
3 Sprints
“Stand up” meetings at beginning of each class
Retrospective at the end of each sprint
OverviewOverview
Definition of ReliabilityDefinition of Reliability
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 SourcesFailure 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 GoalProject Goal
To strengthen the reliability of Web applications by minimizing the number of source content failures.
Attempt to extend work on testing the reliability of websites.
Gain experience doing a research project
Sprint 1Sprint 1
Sprint 1 GoalsSprint 1 Goals
Read relevant research papers
Identify factors that may effect reliability analysis
Determine a system to analyze reliability on
Gather access and error logs
Factors That May EffectFactors That May EffectReliability AnalysisReliability Analysis
Byte Count
User Count
Session Count
Error Count
System to Analyze Reliability OnSystem 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..)
Sprint 2Sprint 2
Sprint 2 GoalsSprint 2 Goals
Collect log files for calculation
Automate processes to extra data (user, session, byte, and error counts)
Convert them into excel format
Log Parser
Sprint 2 ProgressSprint 2 Progress
DNN Logs (10 Websites)
PHP Logs
What is DotNetNuke (DNN)What is DotNetNuke (DNN)
.NET version of Drupal An open source platform for building websites and web applications based on Microsoft .Net technology. Leading open source ASP.NET web content management Has been downloaded over 6 million times ~100 employees 5th Version Founded 2006
Our DNN LogsOur DNN Logs
Logs from 10 Websites Window Server (Same Server) SQL Server 2008 ~1000 unique visitors per day Logs contain
User count Limited Error count
Major ProblemMajor Problem
Our DNN Logs does not contain Session count
Byte count
AlternativeAlternative
Generate our own DNN logs
Sprint 3Sprint 3
Server SideServer Side
Technologies Used Windows XP Professional Microsoft Internet Information Servers (ISS) Microsoft SQL Server 2008 DotNetNuke (DNN)
Logs Generated Client IP’s Byte Counts (Uploaded & Downloaded) Time-Taken Status Code
Generating LogsGenerating Logs
Clients
Web-Crawlers
DotNetNuke Client API
Inducing Errors
ResultsResults
Workload Measurement FactsWorkload Measurement Facts
Server log data consisted of 23 consecutive days of data.
Page Not Found (Error 404) is the most common type of error in our logs, with 46% of total recorded errors.
Accessing forbidden data (Error 403) follows with 41%.
72 unique IPs, 32970 hits total, and each hit associated with average 5020 bytes.
Error/Success RatiosError/Success RatiosHTTPStatus Codes
Description
200 OK
206 Partial Content
302 Found
304 Not Modified
400 Bad Request
401 Unauthorized
403 Forbidden
404 Not Found
500 Internal Server Error
Status Code-Bytes GraphicStatus Code-Bytes Graphic
500-Internal Server Error Profile500-Internal Server Error Profile
Number of errorsNumber of errors
Average Time Taken By Different Average Time Taken By Different ErrorsErrors
ConclusionsConclusions
• By Nelson Model, the site software reliability is R = 0.966, or that 96.6% of access to website is successful.
• This model also shows that MTBF=29.6 hits or the site averages one error for every 29.6 hits.
• From the number of errors chart, we can see that Server errors are very few among the other errors which shows what the reliability of the DNN server is.
Conclusions
Our model Previous Model[1]
23 days data 26 days data
96.6 success 96.2 success
29.6 hits/error 26.6 hits/error
148,579 bytes per error
273,927 bytes per error
[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.