Improving Web Navigation Usability by Comparing Actual and Anticipated Usage

by

We present a new method to identify navigation related Web usability problems based on comparing actual and anticipated usage patterns. The actual usage patterns can be extracted from Web server logs routinely recorded for operational websites by first processing the log data to identify users, user sessions, and user task-oriented transactions, and then applying a usage mining algorithm to discover patterns among actual usage paths. The anticipated usage, including information about both the path and time required for user-oriented tasks, is captured by our ideal user interactive path models constructed by cognitive experts based on their cognition of user behavior.

The comparison is performed via the mechanism of test MY SQL for checking results and identifying user navigation difficulties. The deviation data produced from this comparison can help us discover usability issues and suggest corrective actions to improve usability. A software tool was developed to automate a significant part of the activities involved. With an experiment on a small service-oriented website, we identified usability problems, which were cross-validated by domain experts, and quantified usability improvement by the higher task success rate and lower time and effort for given tasks after suggested corrections were implemented. This case study provides an initial validation of the applicability and effectiveness of our method.

1.2 INTRODUCTION

As the World Wide Web becomes prevalent today, building and ensuring easy-to-use Web systems is becoming a core competency for business survival. Usability is defined as the effectiveness, efficiency, and satisfaction with which specific users can complete specific tasks in a particular environment. Three basic Web design principles, i.e., structural firmness, functional convenience, and presentational delight, were identified to help improve users’ online experience. Structural firmness relates primarily to the characteristics that influence the website security and performance. Functional convenience refers to the availability of convenient characteristics, such as a site’s ease of use and ease of navigation, that help users’ interaction with the interface. Presentational delight refers to the website characteristics that stimulate users’ senses. Usability engineering provides methods for measuring usability and for addressing usability issues. Heuristic evaluation by experts and user-centered testing are typically used to identify usability issues and to ensure satisfactory usability.

However, significant challenges exist, including 1) accuracy of problem identification due to false alarms common in expert evaluation 2) unrealistic evaluation of usability due to differences between the testing environment and the actual usage environment, and 3) increased cost due to the prolonged evolution and maintenance cycles typical for many Web applications. On the other hand, log data routinely kept at Web servers represent actual usage. Such data have been used for usage-based testing and quality assurance and also for understanding user behavior and guiding user interface design.

Server-side logs can be automatically generated by Web servers, with each entry corresponding to a user request. By analyzing these logs, Web workload was characterized and used to suggest performance enhancements for Internet Web servers. Because of the vastly uneven Web traffic, massive user population, and diverse usage environment, coverage-based testing is insufficient to ensure the quality of Web applications. Therefore, server-side logs have been used to construct Web usage models for usage-based Web testing or to automatically generate test cases accordingly to improve test efficiency.

1.3 LITRATURE SURVEY

WEB USABILITY PROBE: A TOOL FOR SUPPORTING REMOTE USABILITY EVALUATION OF WEB SITES

PUBLICATION: Human-Computer Interaction—INTERACT 2011. New York, NY, USA: Springer, 2011,pp. 349–357.

AUTHORS: T. Carta, F. Patern`o, and V. F. D. Santana

EXPLANATION:

Usability evaluation of Web sites is still a difficult and time-consuming task, often performed manually. This paper presents a tool that supports remote usability evaluation of Web sites. The tool considers client-side data on user interactions and JavaScript events. In addition, it allows the definition of custom events, giving evaluators the flexibility to add specific events to be detected and considered in the evaluation. The tool supports evaluation of any Web site by exploiting a proxy-based architecture and enables the evaluator to perform a comparison between actual user behavior and an optimal sequence of actions.

SUPPORTING ACTIVITY MODELLING FROM ACTIVITY TRACES

PUBLICATION: Expert Syst., vol. 29, no. 3, pp. 261–275, 2012.

AUTHORS: O. L. Georgeon, A. Mille, T. Bellet, B. Mathern, and F. E. Ritter,

EXPLANATION:

We present a new method and tool for activity modelling through qualitative sequential data analysis. In particular, we address the question of constructing a symbolic abstract representation of an activity from an activity trace. We use knowledge engineering techniques to help the analyst build ontology of the activity, that is, a set of symbols and hierarchical semantics that supports the construction of activity models. The ontology construction is pragmatic, evolutionist and driven by the analyst in accordance with their modelling goals and their research questions. Our tool helps the analyst define transformation rules to process the raw trace into abstract traces based on the ontology. The analyst visualizes the abstract traces and iteratively tests the ontology, the transformation rules and the visualization format to confirm the models of activity. With this tool and this method, we found innovative ways to represent a car-driving activity at different levels of abstraction from activity traces collected from an instrumented vehicle. As examples, we report two new strategies of lane changing on motorways that we have found and modelled with this approach.

TOOLS FOR REMOTE USABILITY EVALUATION OF WEB APPLICATIONS THROUGH BROWSER LOGS AND TASK MODELS

PUBLICATION: Behavior Res.Methods, Instrum., Comput., vol. 35, no. 3, pp. 369–378, 2003

AUTHORS: L. Paganelli and F. Patern`o,

EXPLANATION:

The dissemination of Web applications is extensive and still growing. The great penetration of Web sites raises a number of challenges for usability evaluators. Video-based analysis can be rather expensive and may provide limited results. In this article, we discuss what information can be provided by automatic tools able to process the information contained in browser logs and task models. To this end, we present a tool that can be used to compare log files of user behavior with the task model representing the actual Web site design, in order to identify where users’ interactions deviate from those envisioned by the system design.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

Previous studies usability has long been addressed and discussed, when people navigate the Web they often encounter a number of usability issues. This is also due to the fact that Web surfers often decide on the spur of the moment what to do and whether to continue to navigate in a Web site. Usability evaluation is thus an important phase in the deployment of Web applications. For this purpose automatic tools are very useful to gather larger amount of usability data and support their analysis.

Remote evaluation implies that users and evaluators are separated in time and/or space. This is important in order to analyse users in their daily environments and decreases the costs of the evaluation without requiring the use of specific laboratories and asking the users to move. In addition, tools for remote Web usability evaluation should be sufficiently general so that they can be used to analyse user behaviour even when using various browsers or applications developed using different toolkits. We prefer logging on the client-side in order to be able to capture any user-generated events, which can provide useful hints regarding possible usability problems.

Existing approaches have been used to support usability evaluation. An example was WebRemUsine, which was a tool for remote usability evaluation of Web applications through browser logs and task models. Propp and Frorbrig have used task models for supporting usability evaluation of a different type of application: cooperative behaviour of people interacting in smart environments. A different use of models is in the authors discuss how task models can enhance visualization of the usability test log. In our case we do not require the effort of developing models to apply our tool. We only require that the designer provides an example of optimal use associated with each of the relevant tasks. The tool will then compare the logs with the actual use with the optimal log in order to identify deviations, which may indicate potential usability problems.

2.1.1 DISADVANTAGES:

Web navigate used a logger to collect data from a user session test on a Web interface prototype running on a PDA simulator in order to evaluate different types of Web navigation tools and identify the best one for small display devices.

Users were asked to find the answer to specific questions using different types of navigation tools to move from one page to another. A database was used to store users’ actions, but they logged only the answer given by the user to each specific question. Moreover they stored separately every term searched by the user by means of the internal search tool.

Client-side data encounters different challenges regarding the identification of the elements that users are interacting with, how to manage element identification when the page is changed dynamically, how to manage data logging when users are going from one page to another, amongst others. The following are some of the solutions we adopted in order to deal with these issues.

2.2 PROPOSED SYSTEM:

We propose a new method to identify navigation related usability problems by comparing Web usage patterns extracted from server logs against anticipated usage represented in some cognitive user models (RQ2). Fig. 1 shows the architecture of our method. It includes three major modules: Usage Pattern Extraction, IUIP Modeling, and Usability Problem Identification. First, we extract actual navigation paths from server logs and discover patterns for some typical events. In parallel, we construct IUIP models for the same events. IUIP models are based on the cognition of user behavior and can represent anticipated paths for specific user-oriented tasks.

Our IUIP models are based on the cognitive models surveyed in Section II, particularly the ACT-R model. Due to the complexity of ACT-R model development and the low-level rule based programming language it relies on we constructed our own cognitive architecture and supporting tool based on the ideas from ACT-R. In general, the user behavior patterns can be traced with a sequence of states and transitions. Our IUIP consists of a number of states and transitions. For a particular goal, a sequence of related operation rules can be specified for a series of transitions. Our IUIP model specifies both the path and the benchmark interactive time (no more than a maximum time) for some specific states (pages). The benchmark time can first be specified based on general rules for common types of Web pages. Humans usually try to complete their tasks in the most efficient manner by attempting to maximize their returns while minimizing the cost.

Typically, experts and novices will have different task performance. Novices need to learn task specific knowledge while performing the task, but experts can complete the task in the most efficient manner. Based on this cognitive mechanism, IUIP models our method is cost-effective. It would be particularly valuable in the two common situations, where an adequate number of actual users cannot be involved in testing and cognitive experts are in short supply. Server logs in our method represent real users’ operations in natural working conditions, and our IUIP models injected with human behavior cognition represent part of cognitive experts’ work. We are currently integrating these modeling and analysis tools into a tool suite that supports measurement, analysis, and overall quality improvement for Web applications.

2.2.1 ADVANTAGES:

1) Logical deviation calculation:

a) When the path choice anticipated by the IUIP model is available but not selected, a single deviation is counted.

b) Sum up all the above deviations over all the selected user transactions for each page.

2) Temporal deviation calculation:

a) When a user spends more time at a specific page than the benchmark specified for the corresponding state in the IUIP model, a single deviation is counted.

b) Sum up all the above deviations over all the selected user transactions for each page.

The successive pages related to furniture categories are grouped into a dashed box. The pages with deviations and the unanticipated follow up pages below them are marked with solid rectangular boxes. Those unanticipated follow up pages will not be used themselves for deviation calculations to avoid double counting.

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v    Processor                                 –    Pentium –IV

  • Speed                                      –    1.1 GHz
    • RAM                                       –    256 MB (min)
    • Hard Disk                               –   20 GB
    • Floppy Drive                           –    1.44 MB
    • Key Board                              –    Standard Windows Keyboard
    • Mouse                                     –    Two or Three Button Mouse
    • Monitor                                   –    SVGA

 

2.3.2 SOFTWARE REQUIREMENTS:

  • Operating System                   :           Windows XP or Win7
  • Front End                                :           JAVA JDK 1.7
  • Back End                                :           MYSQL Server
  • Server                                      :           Apache Tomact Server
  • Script                                       :           JSP Script
  • Document                               :           MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

  • The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system
  • The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.
  • DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.
  • DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data’s in the physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

  1. All processes must have at least one data flow in and one data flow out.
  2. All processes should modify the incoming data, producing new forms of outgoing data.
  3. Each data store must be involved with at least one data flow.
  4. Each external entity must be involved with at least one data flow.
  5. A data flow must be attached to at least one process.


3.1 ARCHITECTURE DIAGRAM

3.2 DATAFLOW DIAGRAM

UML DIAGRAMS:

3.2 USE CASE DIAGRAM:

3.3 CLASS DIAGRAM:

3.4 SEQUENCE DIAGRAM:

3.5 ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

IUIP MODELS:

Our IUIP model specifies both the path and the benchmark interactive time (no more than a maximum time) for some specific states (pages). The benchmark time can first be specified based on general rules for common types of Web pages. For example, human factors guidelines specify the upper bound for the response time to mitigate the risk that users will lose interest in a website. Humans usually try to complete their tasks in the most efficient manner by attempting to maximize their returns while minimizing the cost, experts and novices will have different task performance. Novices need to learn task specific knowledge while performing the task, but experts can complete the task in the most efficient manner on this cognitive mechanism, IUIP models need to be constructed individually for novices and experts by cognitive experts by utilizing their domain expertise and their knowledge of different users’ interactive behavior.

We can adapt the durations by performing iterative tests with different users Diagrammatic notation methods and tools are often used to support interaction modeling and task performance evaluation IUIP model construction and reuse, we used C++ and XML to develop our IUIP modeling tool based on the open-source visual diagram software DIA. DIA allows users to draw customized diagrams, such as UML, data flow, and other diagrams. Existing shapes and lines in DIA form part of the graphic notations in our IUIP models. New ones can be easily added by writing simple XML files. The operations, operation rules, and computation rules can be embedded into the graphic notations with XML schema we defined to form our IUIP symbols. Currently, about 20 IUIP symbols have been created to represent typical Web interactions. IUIP symbols used in subsequent examples are explained at the bottom of cognitive experts can use our IUIP modeling tool to develop various IUIP models for different Web applications.

The actual users’ navigation trails we extracted from the aggregated trail tree are compared against corresponding IUIP models automatically. This comparison will yield a set of deviations between the two. We can identify some common problems of actual users’ interaction with the Web application by focusing on deviations that occur frequently. Combined with expertise in product internal and contextual information, our results can also help identify the root causes of some usability problems existing in the Web design. Based on logical choices made and time spent by users at each page, the calculation of deviations between actual users’ usage patterns and IUIP can be divided into two parts:

1) Logical deviation calculation:

a) When the path choice anticipated by the IUIP model is available but not selected, a single deviation is counted.

b) Sum up all the above deviations over all the selected user transactions for each page.

2) Temporal deviation calculation:

a) When a user spends more time at a specific page than the benchmark specified for the corresponding state in the IUIP model, a single deviation is counted.

b) Sum up all the above deviations over all the selected user transactions for each page.

The IUIP model for the task “First Selection” is shown on the top. The corresponding user Trail 7, a part of a trail tree extracted from log data, is presented under it. The node in the tree is annotated with the number of users having reached the node across the same trail prefix. The successive pages related to furniture categories are grouped into a dashed box. The pages with deviations and the unanticipated follow up pages below them are marked with solid rectangular boxes. Those unanticipated followup pages will not be used themselves for deviation calculations to avoid double counting.

4.1 ALGORITHM

TRAIL TREE USAGE MINING ALGORITHM

The transactions identified from each user session form a collection of paths use the trie data structure to merge the paths along common prefixes. A trie, or a prefix tree, is an ordered tree used to store an associative array where the keys are usually strings. All the descendants of a node have a common prefix of the string associated with that node. The root is associated with the empty string. We adapted the trie algorithm to construct a tree structure that also captures user visit frequencies, which is called a trail tree in our work. In a trail tree, a complete path from the root to a leaf node is called a trail.

The leaf nodes of the trail tree are also annotated with the trail names. The transaction paths extracted from the Web server log are shown in the table to its left, together with path occurrence frequencies. Paths 1, 4, and 5 have the common first node a; therefore, they were merged together. For the second node of this subtree, Paths 1 and 4 both accessed Page b; therefore, the two paths were combined at Node b. Finally, Paths 1 and 4 were merged into a single trail, Trail 1, although Path 1 terminates at Node e. By the same method, the other paths can be integrated into the trail tree. The number at each edge indicates the number of users reaching the next node across the same trail prefix.

Based on the aggregated trail tree, further mining can be performed for some “interesting” pattern discovery. Typically, good mining results require a close interaction of the human experts to specify the characteristics that make navigation patterns interesting. In our method, we focus on the paths which are used by a sufficient number of users to finish a specific task. The paths can be initially prioritized by their usage frequencies and selected by using a threshold specified by the experts. Application-domain knowledge and contextual information, such as criticality of specific tasks, user privileges, etc., can also be used to identified “interesting” patterns. For the FG 2009 website, we extracted 30 trails each for Tasks 1, 2, and 3, and 5 trails for Task 4.

4.2 MODULES:

COGNITIVE USER MODEL:

WEB SERVER USER LOG:

USAGE PATTERN EXTRACTION:

USABILITY MEASURING:

4.3 MODULE DESCRIPTION:

COGNITIVE USER MODEL:

User Models is a growing need to incorporate insights from cognitive science about the mechanisms, strengths, and limits of human perception and cognition to understand the human factors involved in user interface design in the various constraints on cognition (e.g., system complexity) and the mechanisms and patterns of strategy selection can help human factor engineers develop solutions and apply technologies that are better suited to human abilities.

Commonly used cognitive models include GOMS, EPIC, and ACT-R. The GOMS model consists of Goals, Operators, Methods, and Selection rules. As the high-level architecture, GOMS describes behavior and defines interactions as a static sequence of human actions. As the low-level cognitive architecture, EPIC (Executive-Process/Interactive Control) and ACT-R (Adaptive Control of Thought-Rational) can be taken as the specific implementation of the high-level architecture.

They provide detailed information about how to simulate human processing and cognition important feature of these low-level cognitive architectures is that they are all implemented as computer programming systems so that cognitive models may be specified, executed, and their outputs (e.g., error rates and response latencies) compared with human performance data.

WEB SERVER USER LOG:

Server logs have also been used by organizations to learn about the usability of their products. For example, search queries can be extracted from server logs to discover user information needs for usability task analysis. There are many advantages to using server logs for usability studies. Logs can provide insight into real users performing actual tasks in natural working conditions versus in an artificial setting of a lab. Logs also represent the activities of many users over a long period of time versus the small sample of users in a short time span in typical lab testing. Data preparation techniques and algorithms can be used to process the raw Web server logs, and then mining can be performed to discover users’ visitation patterns for further usability analysis.

For example, organizations can mine server-side logs to predict users’ behavior and context to satisfy users’ revisitiation patterns can be discovered by mining server logs to develop guidelines for browser history mechanism that can be used to reduce users’ cognitive and physical effort Client-side logs can capture accurate comprehensive usage data for usability analysis, because they allow low-level user interaction events such as keystrokes and mouse movements to be recorded.

For example, using these client-side data, the evaluator can accurately measure time spent on particular tasks or pages as well as study the use of “back” button and user click streams. Such data are often used with task based approaches and models for usability analysis by comparing discrepancies between the designer’s anticipation and a user’s actual behavior. However, the evaluator must program the UI, modify Web pages, or use an instrumented browser with plug-in tools or a special proxy server to collect such data.

USAGE PATTERN EXTRACTION:

Web server logs are our data source. Each entry in a log contains the IP address of the originating host, the timestamp, the requested Web page, the referrer, the user agent and other data. Typically, the raw data need to be preprocessed and converted into user sessions and transactions to extract usage patterns.

The data preparation and preprocessing include the following domain-dependent tasks.

1) Data cleaning: This task is usually site-specific and involves removing extraneous references to style files, graphics, or sound files that may not be important for the purpose of our analysis.

2) User identification: The remaining entries are grouped by individual users. Because no user authentication and cookie information is available in most server logs, we used the combination of IP, user agent, and referrer fields to identify unique users.

3) User session identification: The activity record of each user is segmented into sessions, with each representing a single visit to a site. Without additional authentication information from users and without the mechanisms such as embedded session IDs, one must rely on heuristics for session identification. For example, we set an elapse time of 15 min between two successive page accesses as a threshold to partition a user activity record into different sessions.

4) Path completion: Client or proxy side caching can often result in missing access references to some pages that have been cached. These missing references can often be heuristically inferred from the knowledge of site topology and referrer information, along with temporal information from server logs.

These tasks are time consuming and computationally intensive, but essential to the successful discovery of usage patterns.

We developed a tool to automate all these tasks except part of path completion. For path completion, the designers or developers first need to manually discover the rules of missing references based on site structure, referrer, and other heuristic information. Once the repeated patterns are identified, this work can be automatically carried out. Our tool can work with server logs of different Web applications by modifying the related parameters in the configuration file. The processed log data are stored into a database for further use.

USABILITY MEASURING:

Our specific results from applying our method to the FG 2009 website we collected Web server access log data for the first three days after its deployment. The server log includes about above 500 entries. After preprocessing the raw log data using our tool, we identified 58 unique users and 81 sessions. Then, we constructed four event models for four typical tasks. We extracted 95 trails for these tasks. Meanwhile, a designer with three-year GUI design experience and an expert with five-year experience with human factors practice for the Web constructed four IUIP models for the same tasks based on their cognition of users’ interactive behavior. By checking the extracted usage patterns against the four IUIP models, we obtained logical and temporal deviations shown in Tables I and II and identified 17 usability issues or potential usability problems. Some usability issues were identified by both logical and temporal deviation analyses. Next, we further analyze these deviations for usability problem identification and improvement.

In Table I, 16 deviations took place in the page “index.php.” The unanticipated followup page is the page “login.php,” followed by the page “index.php?f=t” (login failure). Further reviewing the index page, we found that the page design is too simplistic: No instruction was provided to help users to login or register. We inferred that some users with limited online shopping experience were trying to use their regular email addresses and passwords to log in to the FG 2009 website.

We also found some structure design issues. For example, we observed that some users repeatedly visited the page “Selection Rules.” It is likely that when the users were not permitted to select any furniture in some categories (the FG website limited each user to select one piece of furniture under each category), they had to go to the page “Selection Rules” to find the reasons. To reduce these redundant operations and improve user experience, the help function for selection rules should be redesigned to make it more convenient for users to consult.

CHAPTER 5

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

The feasibility of the project is analyzed in this phase and business proposal is put forth with a very general plan for the project and some cost estimates. During system analysis the feasibility study of the proposed system is to be carried out. This is to ensure that the proposed system is not a burden to the company.  For feasibility analysis, some understanding of the major requirements for the system is essential.

Three key considerations involved in the feasibility analysis are 

  • ECONOMICAL FEASIBILITY
  • TECHNICAL FEASIBILITY
  • SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:     

This study is carried out to check the economic impact that the system will have on the organization. The amount of fund that the company can pour into the research and development of the system is limited. The expenditures must be justified. Thus the developed system as well within the budget and this was achieved because most of the technologies used are freely available. Only the customized products had to be purchased.

 

5.1.2 TECHNICAL FEASIBILITY   

This study is carried out to check the technical feasibility, that is, the technical requirements of the system. Any system developed must not have a high demand on the available technical resources. This will lead to high demands on the available technical resources. This will lead to high demands being placed on the client. The developed system must have a modest requirement, as only minimal or null changes are required for implementing this system.  

5.1.3 SOCIAL FEASIBILITY:  

The aspect of study is to check the level of acceptance of the system by the user. This includes the process of training the user to use the system efficiently. The user must not feel threatened by the system, instead must accept it as a necessity. The level of acceptance by the users solely depends on the methods that are employed to educate the user about the system and to make him familiar with it. His level of confidence must be raised so that he is also able to make some constructive criticism, which is welcomed, as he is the final user of the system.

5.2 SYSTEM TESTING:

Testing is a process of checking whether the developed system is working according to the original objectives and requirements. It is a set of activities that can be planned in advance and conducted systematically. Testing is vital to the success of the system. System testing makes a logical assumption that if all the parts of the system are correct, the global will be successfully achieved. In adequate testing if not testing leads to errors that may not appear even many months.

This creates two problems, the time lag between the cause and the appearance of the problem and the effect of the system errors on the files and records within the system. A small system error can conceivably explode into a much larger Problem. Effective testing early in the purpose translates directly into long term cost savings from a reduced number of errors. Another reason for system testing is its utility, as a user-oriented vehicle before implementation. The best programs are worthless if it produces the correct outputs.

5.2.1 UNIT TESTING:

Description Expected result
Test for application window properties. All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations. All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

A program represents the logical elements of a system. For a program to run satisfactorily, it must compile and test data correctly and tie in properly with other programs. Achieving an error free program is the responsibility of the programmer. Program  testing  checks  for  two  types  of  errors:  syntax  and  logical. Syntax error is a program statement that violates one or more rules of the language in which it is written. An improperly defined field dimension or omitted keywords are common syntax errors. These errors are shown through error message generated by the computer. For Logic errors the programmer must examine the output carefully.

5.1.2 FUNCTIONAL TESTING:

Functional testing of an application is used to prove the application delivers correct results, using enough inputs to give an adequate level of confidence that will work correctly for all sets of inputs. The functional testing will need to prove that the application works for each client type and that personalization function work correctly.When a program is tested, the actual output is compared with the expected output. When there is a discrepancy the sequence of instructions must be traced to determine the problem.  The process is facilitated by breaking the program into self-contained portions, each of which can be checked at certain key points. The idea is to compare program values against desk-calculated values to isolate the problems.

Description Expected result
Test for all modules. All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group. The result after execution should give the accurate result.


5.1. 3 NON-FUNCTIONAL TESTING:

 The Non Functional software testing encompasses a rich spectrum of testing strategies, describing the expected results for every test case. It uses symbolic analysis techniques. This testing used to check that an application will work in the operational environment. Non-functional testing includes:

  • Load testing
  • Performance testing
  • Usability testing
  • Reliability testing
  • Security testing

5.1.4 LOAD TESTING:

An important tool for implementing system tests is a Load generator. A Load generator is essential for testing quality requirements such as performance and stress. A load can be a real load, that is, the system can be put under test to real usage by having actual telephone users connected to it. They will generate test input data for system test.

Description Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received. Should designate another active node as a Server.


5.1.5 PERFORMANCE TESTING:

Performance tests are utilized in order to determine the widely defined performance of the software system such as execution time associated with various parts of the code, response time and device utilization. The intent of this testing is to identify weak points of the software system and quantify its shortcomings.

Description Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.   Should handle large input values, and produce accurate result in a  expected time.  


5.1.6 RELIABILITY TESTING:

The software reliability is the ability of a system or component to perform its required functions under stated conditions for a specified period of time and it is being ensured in this testing. Reliability can be expressed as the ability of the software to reveal defects under testing conditions, according to the specified requirements. It the portability that a software system will operate without failure under given conditions for a given time interval and it focuses on the behavior of the software element. It forms a part of the software quality control team.

Description Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application. In case of failure of  the server an alternate server should take over the job.


5.1.7 SECURITY TESTING:

Security testing evaluates system characteristics that relate to the availability, integrity and confidentiality of the system data and services. Users/Clients should be encouraged to make sure their security needs are very clearly known at requirements time, so that the security issues can be addressed by the designers and testers.

  Description Expected result
Checking that the user identification is authenticated. In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers. The peers should know group key in the same group.


5.1.8 WHITE BOX TESTING:

White  box  testing,  sometimes called  glass-box  testing is  a test  case  design method  that  uses  the  control  structure  of the procedural  design  to  derive  test  cases. Using  white  box  testing  method,  the software  engineer  can  derive  test  cases. The White box testing focuses on the inner structure of the software structure to be tested.

Description Expected result
Exercise all logical decisions on their true and false sides. All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds. All the loops must be finite.
Exercise internal data structures to ensure their validity. All the data structures must be valid.


5.1.9 BLACK BOX TESTING:

Black box testing, also called behavioral testing, focuses on the functional requirements of the software.  That  is,  black  testing  enables  the software engineer  to  derive  sets  of  input  conditions  that  will  fully  exercise  all  functional requirements  for  a  program.  Black box testing is not alternative to white box techniques.  Rather  it  is  a  complementary  approach  that  is  likely  to  uncover  a different  class  of  errors  than  white box  methods. Black box testing attempts to find errors which focuses on inputs, outputs, and principle function of a software module. The starting point of the black box testing is either a specification or code. The contents of the box are hidden and the stimulated software should produce the desired results.

Description Expected result
To check for incorrect or missing functions. All the functions must be valid.
To check for interface errors. The entire interface must function normally.
To check for errors in a data structures or external data base access. The database updation and retrieval must be done.
To check for initialization and termination errors. All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 6

6.0 SOFTWARE DESCRIPTION:

 

6.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

 

The Java Programming Language

 

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

  • Simple
    • Architecture neutral
    • Object oriented
    • Portable
    • Distributed     
    • High performance
    • Interpreted     
    • Multithreaded
    • Robust
    • Dynamic
    • Secure     

With most programming languages, you either compile or interpret a program so that you can run it on your computer. The Java programming language is unusual in that a program is both compiled and interpreted. With the compiler, first you translate a program into an intermediate language called Java byte codes —the platform-independent codes interpreted by the interpreter on the Java platform. The interpreter parses and runs each Java byte code instruction on the computer. Compilation happens just once; interpretation occurs each time the program is executed. The following figure illustrates how this works.

You can think of Java byte codes as the machine code instructions for the Java Virtual Machine (Java VM). Every Java interpreter, whether it’s a development tool or a Web browser that can run applets, is an implementation of the Java VM. Java byte codes help make “write once, run anywhere” possible. You can compile your program into byte codes on any platform that has a Java compiler. The byte codes can then be run on any implementation of the Java VM. That means that as long as a computer has a Java VM, the same program written in the Java programming language can run on Windows 2000, a Solaris workstation, or on an iMac.

6.2 THE JAVA PLATFORM:

A platform is the hardware or software environment in which a program runs. We’ve already mentioned some of the most popular platforms like Windows 2000, Linux, Solaris, and MacOS. Most platforms can be described as a combination of the operating system and hardware. The Java platform differs from most other platforms in that it’s a software-only platform that runs on top of other hardware-based platforms.

The Java platform has two components:

  • The Java Virtual Machine (Java VM)
  • The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The Java API is a large collection of ready-made software components that provide many useful capabilities, such as graphical user interface (GUI) widgets. The Java API is grouped into libraries of related classes and interfaces; these libraries are known as packages. The next section, What Can Java Technology Do? Highlights what functionality some of the packages in the Java API provide.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

Native code is code that after you compile it, the compiled code runs on a specific hardware platform. As a platform-independent environment, the Java platform can be a bit slower than native code. However, smart compilers, well-tuned interpreters, and just-in-time byte code compilers can bring performance close to that of native code without threatening portability.

6.3 WHAT CAN JAVA TECHNOLOGY DO?

The most common types of programs written in the Java programming language are applets and applications. If you’ve surfed the Web, you’re probably already familiar with applets. An applet is a program that adheres to certain conventions that allow it to run within a Java-enabled browser.

However, the Java programming language is not just for writing cute, entertaining applets for the Web. The general-purpose, high-level Java programming language is also a powerful software platform. Using the generous API, you can write many types of programs.

An application is a standalone program that runs directly on the Java platform. A special kind of application known as a server serves and supports clients on a network. Examples of servers are Web servers, proxy servers, mail servers, and print servers. Another specialized program is a servlet.

A servlet can almost be thought of as an applet that runs on the server side. Java Servlets are a popular choice for building interactive web applications, replacing the use of CGI scripts. Servlets are similar to applets in that they are runtime extensions of applications. Instead of working in browsers, though, servlets run within Java Web servers, configuring or tailoring the server.

How does the API support all these kinds of programs? It does so with packages of software components that provides a wide range of functionality. Every full implementation of the Java platform gives you the following features:

  • The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
  • Applets: The set of conventions used by applets.
  • Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
  • Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
  • Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
  • Software components: Known as JavaBeansTM, can plug into existing component architectures.
  • Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
  • Java Database Connectivity (JDBCTM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

 

6.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

We can’t promise you fame, fortune, or even a job if you learn the Java programming language. Still, it is likely to make your programs better and requires less effort than other languages. We believe that Java technology will help you do the following:

  • Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
  • Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
  • Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
  • Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
  • Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure JavaTM Product Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
  • Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
  • Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

 

6.5 ODBC:

 

Microsoft Open Database Connectivity (ODBC) is a standard programming interface for application developers and database systems providers. Before ODBC became a de facto standard for Windows programs to interface with database systems, programmers had to use proprietary languages for each database they wanted to connect to. Now, ODBC has made the choice of the database system almost irrelevant from a coding perspective, which is as it should be. Application developers have much more important things to worry about than the syntax that is needed to port their program from one database to another when business needs suddenly change.

Through the ODBC Administrator in Control Panel, you can specify the particular database that is associated with a data source that an ODBC application program is written to use. Think of an ODBC data source as a door with a name on it. Each door will lead you to a particular database. For example, the data source named Sales Figures might be a SQL Server database, whereas the Accounts Payable data source could refer to an Access database. The physical database referred to by a data source can reside anywhere on the LAN.

The ODBC system files are not installed on your system by Windows 95. Rather, they are installed when you setup a separate database application, such as SQL Server Client or Visual Basic 4.0. When the ODBC icon is installed in Control Panel, it uses a file called ODBCINST.DLL. It is also possible to administer your ODBC data sources through a stand-alone program called ODBCADM.EXE. There is a 16-bit and a 32-bit version of this program and each maintains a separate list of ODBC data sources.

From a programming perspective, the beauty of ODBC is that the application can be written to use the same set of function calls to interface with any data source, regardless of the database vendor. The source code of the application doesn’t change whether it talks to Oracle or SQL Server. We only mention these two as an example. There are ODBC drivers available for several dozen popular database systems. Even Excel spreadsheets and plain text files can be turned into data sources. The operating system uses the Registry information written by ODBC Administrator to determine which low-level ODBC drivers are needed to talk to the data source (such as the interface to Oracle or SQL Server). The loading of the ODBC drivers is transparent to the ODBC application program. In a client/server environment, the ODBC API even handles many of the network issues for the application programmer.

The advantages of this scheme are so numerous that you are probably thinking there must be some catch. The only disadvantage of ODBC is that it isn’t as efficient as talking directly to the native database interface. ODBC has had many detractors make the charge that it is too slow. Microsoft has always claimed that the critical factor in performance is the quality of the driver software that is used. In our humble opinion, this is true. The availability of good ODBC drivers has improved a great deal recently. And anyway, the criticism about performance is somewhat analogous to those who said that compilers would never match the speed of pure assembly language. Maybe not, but the compiler (or ODBC) gives you the opportunity to write cleaner programs, which means you finish sooner. Meanwhile, computers get faster every year.

6.6 JDBC:

In an effort to set an independent database standard API for Java; Sun Microsystems developed Java Database Connectivity, or JDBC. JDBC offers a generic SQL database access mechanism that provides a consistent interface to a variety of RDBMSs. This consistent interface is achieved through the use of “plug-in” database connectivity modules, or drivers. If a database vendor wishes to have JDBC support, he or she must provide the driver for each platform that the database and Java run on.

To gain a wider acceptance of JDBC, Sun based JDBC’s framework on ODBC. As you discovered earlier in this chapter, ODBC has widespread support on a variety of platforms. Basing JDBC on ODBC will allow vendors to bring JDBC drivers to market much faster than developing a completely new connectivity solution.

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

The remainder of this section will cover enough information about JDBC for you to know what it is about and how to use it effectively. This is by no means a complete overview of JDBC. That would fill an entire book.

 

6.7 JDBC Goals:

Few software packages are designed without goals in mind. JDBC is one that, because of its many goals, drove the development of the API. These goals, in conjunction with early reviewer feedback, have finalized the JDBC class library into a solid framework for building database applications in Java.

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

The designers felt that their main goal was to define a SQL interface for Java. Although not the lowest database interface level possible, it is at a low enough level for higher-level tools and APIs to be created. Conversely, it is at a high enough level for application programmers to use it confidently. Attaining this goal allows for future tool vendors to “generate” JDBC code and to hide many of JDBC’s complexities from the end user.

SQL Conformance

SQL syntax varies as you move from database vendor to database vendor. In an effort to support a wide variety of vendors, JDBC will allow any query statement to be passed through it to the underlying database driver. This allows the connectivity module to handle non-standard functionality in a manner that is suitable for its users.

JDBC must be implemental on top of common database interfaces

The JDBC SQL API must “sit” on top of other common SQL level APIs. This goal allows JDBC to use existing ODBC level drivers by the use of a software interface. This interface would translate JDBC calls to ODBC and vice versa.

  1. Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

  • Keep it simple

This goal probably appears in all software design goal listings. JDBC is no exception. Sun felt that the design of JDBC should be very simple, allowing for only one method of completing a task per mechanism. Allowing duplicate functionality only serves to confuse the users of the API.

  • Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

  • Keep the common cases simple

Because more often than not, the usual SQL calls used by the programmer are simple SELECT’s, INSERT’s, DELETE’s and UPDATE’s, these queries should be simple to perform with JDBC. However, more complex SQL statements should also be possible.

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple                                     Architecture-neutral

Object-oriented                       Portable

Distributed                              High-performance

Interpreted                              Multithreaded

Robust                                     Dynamic Secure

Java is also unusual in that each Java program is both compiled and interpreted. With a compile you translate a Java program into an intermediate language called Java byte codes the platform-independent code instruction is passed and run on the computer.

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

Java Program
Compilers
Interpreter
My Program

6.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

The IP layer provides a connectionless and unreliable delivery system. It considers each datagram independently of the others. Any association between datagram must be supplied by the higher layers. The IP layer supplies a checksum that includes its own header. The header includes the source and destination addresses. The IP layer handles routing through an Internet. It is also responsible for breaking up large datagram into smaller ones for transmission and reassembling them at the other end.

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

A service exists on a host, and is identified by its port. This is a 16 bit number. To send a message to a server, you send it to the port for that service of the host that it is running on. This is not location transparency! Certain of these ports are “well known”.

Sockets:

A socket is a data structure maintained by the system to handle network connections. A socket is created using the call socket. It returns an integer that is like a file descriptor. In fact, under Windows, this handle can be used with Read File and Write File functions.

#include <sys/types.h>
#include <sys/socket.h>
int socket(int family, int type, int protocol);

Here “family” will be AF_INET for IP communications, protocol will be zero, and type will depend on whether TCP or UDP is used. Two processes wishing to communicate over a network create a socket each. These are similar to two ends of a pipe – but the actual pipe does not yet exist.

6.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

 

6.8.1. Map Visualizations:

Charts showing values that relate to geographical areas. Some examples include: (a) population density in each state of the United States, (b) income per capita for each country in Europe, (c) life expectancy in each country of the world. The tasks in this project include: Sourcing freely redistributable vector outlines for the countries of the world, states/provinces in particular countries (USA in particular, but also other areas);

Creating an appropriate dataset interface (plus default implementation), a rendered, and integrating this with the existing XYPlot class in JFreeChart; Testing, documenting, testing some more, documenting some more.

6.8.2. Time Series Chart Interactivity

Implement a new (to JFreeChart) feature for interactive time series charts — to display a separate control that shows a small version of ALL the time series data, with a sliding “view” rectangle that allows you to select the subset of the time series data to display in the main chart.

6.8.3. Dashboards

There is currently a lot of interest in dashboard displays. Create a flexible dashboard mechanism that supports a subset of JFreeChart chart types (dials, pies, thermometers, bars, and lines/time series) that can be delivered easily via both Java Web Start and an applet.

 

6.8.4. Property Editors

The property editor mechanism in JFreeChart only handles a small subset of the properties that can be set for charts. Extend (or reimplement) this mechanism to provide greater end-user control over the appearance of the charts.

CHAPTER 8

8.1 CONCLUSION:

We have developed a new method for the identification and improvement of navigation-related Web usability problems by checking extracted usage patterns against cognitive user models. As demonstrated by our case study, our method can identify areas with usability issues to help improve the usability of Web systems. Once a website is operational, our method can be continuously applied and drive ongoing refinements. In contrast with traditional software products and systems, Web based applications have shortened development cycles and prolonged maintenance cycles. Our method can contribute significantly to continuous usability improvement over these prolonged maintenance cycles. The usability improvement in successive iterations can be quantified by the progressively better effectiveness (higher task completion rate) and efficiency (less time for given tasks).

Our method is not intended to and cannot replace heuristic usability evaluation by experts and user-centered usability testing. It complements these traditional usability practices and can be incorporated into an integrated strategy for Web usability assurance. With automated tool support for a significant part of the activities involved, our method is cost-effective. It would be particularly valuable in the two common situations, where an adequate number of actual users cannot be involved in testing and cognitive experts are in short supply. Server logs in our method represent real users’ operations in natural working conditions, and our IUIP models injected with human behavior cognition represent part of cognitive experts’ work. We are currently integrating these modeling and analysis tools into a tool suite that supports measurement, analysis, and overall quality improvement for Web applications.

8.2 FUTURE ENHANCEMENT: In the future, we should and must carry out validation studies with large-scale Web applications. We also plan to explore additional approaches to discover Web usage patterns and related usability problems generalizable to other interesting domains. For example, we have already started exploring deviation calculation and analysis at the trail level instead of at the individual page level. Such analyses might be more meaningful and yield more interesting results for Web applications with complex structure and operation sequences. Our IUIP modeling architecture and supporting tools also need to be further enhanced and optimized for more complex tasks. We will also further expand our usability research to cover more usability aspects to improve Web users’ overall satisfaction.