Reliability study and analysis on open source enterprise resource planning software package

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Reliability study and analysis on open source enterprise resource planning software package

  1. 1. R.V. College of Engineering R.V. COLLEGE OF ENGINEERING, BANGALORE-560059 (Autonomous Institution Affiliated to VTU, Belgaum)Reliability Study and Analysis on Open Source Enterprise Resource Planning Software Package MINI PROJECT REPORT Submitted by Mayank Baheti 1RV09IM024 Deepak Rathod 1RV09IM009 Suraj Soni 1RV09IM044 Tanay Agrawal 1RV09IM046 Under the Guidance of Mr. Vikram Bahadurdesai Asst. Professor, IEM Department, R.V. College of Engineering, Bangalore 560059. In Partial fulfilment of the academic requirements of VI Semester B.E Programme in Industrial Engineering and Management 2011-12Department of industrial engineering and management Page 1
  2. 2. R.V. College of Engineering Sl.No Topic Page. No Abstract i. 1. Introduction 7 1.1. Overview to Software Reliability 7 1.2 Overview of Open Source ERP Software 7 1.3. Principles of open source architecture 8 Introduction to open source architecture 81.3.1. Overview Apache open for business (Ofbiz) 9 1.3.2. 1.3.3. Features of Apache open for business(Ofbiz) 10 1.3.4. Different Open Source ERP Software’s 10 1.4. Literature Review 13 1.5. Problem Genesis 15 1.6. Objectives 16 2. Theoretical Concepts and fundamentals 17 2.1. Software reliability modeling 18 Department of industrial engineering and management Page 2
  3. 3. R.V. College of Engineering 2.2. Software reliability modeling classification 19 2.3. Theoretical Comparison of Techniques 21 2.4. Exponential Model 23 3. Methodology 25 3.1. Study of Ofbiz ERP software package 25 3.2. Develop Operational Profile 25 3.3. Testing 25 Performance testing on different operating systems 253.3.1. Performance testing on different web browsers 263.3.2. 3.4. Data Collection 28 3.4.1. Performance testing of different modules of Ofbiz on different Web browsers. 29 3.4.2. Functionality Testing 35 3.4.3. Test cases 36 3.4.4. Ofbiz Defect Tracker 39 Department of industrial engineering and management Page 3
  4. 4. R.V. College of Engineering 3.5. Data analysis 46 4. Conclusions 56 5. Future Scope 57 ReferencesDepartment of industrial engineering and management Page 4
  5. 5. R.V. College of Engineering Abstract Software reliability turns out to be most important part of business today,which plays an important role in assuring the quality of software systems. Softwarereliability is built in a system by performing exhaustive testing. Testing is animportant phase in software development lifecycle and is generally considered tobe costly and tedious. But it is very much essential to ensure the quality of theproduct. The ideal goal of most of the companies is to develop robust software bytesting it cost-effectively. Robustness should be inherently developed along withproduct development rather than incorporating it after the implementation phase.The idea is to test early and to test often. Software reliability is the probability of failure free software operation for aspecified period of time in a specified environment. The high complexity of thesoftware is the major contributing factor of software reliability problems. Softwarereliability is also important factor affecting system reliability. Software reliabilityis an important attribute of software quality, together with functionality, usability,performance, serviceability, capability, install ability, maintainability anddocumentation. Software reliability engineering (SRE) is an emerging discipline,SRE is the application of statistical techniques to specify, predict, estimate andassess the reliability of software based systems. Testing open source apache Ofbiz ERP software gives as opportunity to haveinferences such as reliability, mean time to failure (MTTF) etc, for software systemand gain its credibility in this field. Software Testing is process of executing aprogram with the intent of finding error. A good test case is one that uncovers an asyet undiscovered error. Testing should systematically uncover different classes oferrors in a minimum amount of time and with a minimum amount of effort.Generating test sequences from usage probability distributions, assessing statisticalinferences based on analytical results associated with test process and also deriveDepartment of industrial engineering and management Page 5
  6. 6. R.V. College of Engineeringstopping criterion of test process. But the problem associated in this process is totest the software behavior in different types of environment and measuring thereliability. The purpose of testing can be quality assurance, verification and validation, orreliability estimation. Software testing is a trade-off between budget, time andquality. To predict reliability of software failure data need to be collected duringtesting phase of the software developmental life cycle. So software testing plays acrucial role in estimating the reliability of software system. In this work, OfbizERP software package is tested for its performance on different operating systemsand on different web browsers. Finally functionality test has been conducted bygenerating test cases. This result in identifying different bugs, using work aroundmethods bugs has been fixed. Our experimental efforts lead us to a more practicaland effective approach for software reliability.Department of industrial engineering and management Page 6
  7. 7. R.V. College of Engineering 1.0 INTRODUCTION1.1 Overview of Software ReliabilitySoftware reliability is one of the major software quality attributes, which quantitatively expressesthe continuity of correct service delivery. Reliability models are typically measurement basedmodels, and mostly employed in isolation at the later stage of the software development process.In current practice, early software reliability prediction models are often insufficiently formal tobe analyzable and not usually connected to the target system. Additionally, despite the vast workthat has been done in software reliability, much work is still needed, especially in thecomponent-based development arena regarding availability of software component reliabilityinformation following a clear failure classification scheme. Aiming at addressing these problems,this work contributes a novel reliability prediction technique that leverages reliability analysis inearly stages of software development by taking into account, the component structure exhibitedin the scenarios elicited in the requirements phase and the concurrent nature of component-basedsystems. Following that contribution, this thesis proposes a means to accomplish reliabilitydesign and analysis for model driven engineering following the Model Driven Architecturestandards. By doing that, this research work contributes to the task of systematically integratingreliability modeling from the early to the late stages of software engineering and thussemantically integrating analysis, design and deployment models for reliability into oneenvironment. Open Source Software adoption in large companies is considered to be a relativelyrecent movement. Open Source Software is gaining terrain in large organizations, some see it asjust another development alternative; others see in it a strategic competitive advantage. In spiteof those interests and efforts, techniques available to validate a design against nonfunctionalproperties, particularly reliability, often require significant expertise unrelated to the usualbusiness of engineering software. As reliability measures quantitatively the quality of correctservice delivery, it is probably the most important characteristic for the software engineeringdiscipline1.2 Overview of Enterprise Resource Planning (ERP)An ERP system is fully integrated business management system covering function area of anenterprise like logistics, finance, accounting, production and human resource. It organize andintegrates operation process and information flow to make an optimum use of resources such asDepartment of industrial engineering and management Page 7
  8. 8. R.V. College of Engineeringmen, material, money and machine. ERP is global, tightly integrated close loop business solutionpackage and it’s multifaceted.ERP promises one database, one application and one user interface for entire enterprise, whereonce disparate system ruled, manufacturing, distribution, finance and sales. Taking informationfrom every function, it is a tool that assists employee and manager plan, monitor and control theentire business. A modern ERP system enhance a manufacturing ability to accurately scheduleproduction, fully utilize capacity, reduce inventory and meet promised shipping dates. Fig1.1:- General Model of ERP1.3 Principles of Open Source Architecture1.3.1 IntroductionOpen Source Software (OSS) in general refers to any software whose source code is freelyavailable for distribution. The success and benefits of OSS can be attributed to many factors suchas code modification by any party as the needs arise, promotion of software reliability andDepartment of industrial engineering and management Page 8
  9. 9. R.V. College of Engineeringquality due to peer review and collaboration among many volunteer programmers from differentorganizations, and the fact that the knowledge-base is not bound to a particular organization,which allows for faster development and the likelihood of the software to be available fordifferent platforms.Characteristics of OSS: It is generally acquired freely. Manufacturer or developer has no rightto claim royalties on the distribution or use. Source code is accessible to the user and distributedwith the software. No denial to an individual or to a group to access source code of the software.It has provision of modifications and derivations under the programme’s original name. Rights offacilities attached to the programme must not depend on the programme’s being part of aparticular software distribution. Licensed software can not place restriction on other softwarethat is distributed with it. Distribution of License should not be specific to a product and Licenseshould be technology neutral, etc.1.3.2 Overview of Apache Open for Business (OFBiz)Apache OFBiz (The Apache Open For Business Project) is a community-driven open sourceproject. For many organizations, OFBiz is also the best e-commerce and enterprise resourceplanning (ERP) software available.1. No Licensing Fees: OFBiz is free and open source.2. Credibility: OFBiz users can rely on the organizational, legal, and financial stability that comes with OFBiz being a top-level project at the Apache Software Foundation (ASF).3. Collaboration: OFBiz is licensed under the Apache 2.0 open source license, which is both open and business-friendly, facilitating community-driven, meritocratic collaboration while allowing proprietary derivative applications.4. Flexibility: Users will have complete access to source code it will eliminate "proprietary system" limitations. The entire open source community benefits from making OFBiz as clear, flexible, and reusable as possible.5. Lower Cost: OFBiz can help user to achieve a system that is as good or better than those available from major proprietary ERP vendors at a significantly lower total project cost. With OFBiz, user can budget for custom features and added value rather than license and maintenance fees.6. Scalability: Based on the Java platform, OFBiz has the capacity to scale dramatically as needed.Department of industrial engineering and management Page 9
  10. 10. R.V. College of Engineering7. Third Party Friendly: Enjoy freedom from indefinite vendor lock; with OFBiz, user can fully leverage internal resources and/or any of the dozens of organizations offering quality OFBiz implementation and support services.8. Frequent Updates: Benefit from the active and ongoing contributions of the world-wide OFBiz community.9. Feature Rich: Leverage standards-based tools and components are attractive to user technology staff, yet already integrated into a common framework.10. Expert Leadership and Support: HotWax Media provides system design, project planning and management, along with robust technical muscle to deliver the implementation and support necessary for user’s business.1.3.3 Features of Apache Open for Business (OFBiz)Apache OFBiz applications and brief descriptions Table 1.1: OFBiz applications Accounting Setup your chart of accounts, manage agreements, billing, invoices, Manager payments, and more. Catalog Manager Create catalogs and populate products by categories. Maintain product features, price rules, promotions, subscriptions, reviews, and more. Content Manager Underlying CMS capability that can be customized to manage website content, blogs, surveys, and more. Facility Manager Pick, pack, and ship while maintaining inventory information. Manufacturing MRP, job shop, routing and routing task screens, and BOM screens. Manager Marketing Maintaining mailing lists, manage online marketing campaigns that are Manager fully integrated with e-commerce. Order Manager Manage purchase and sales orders, create orders, handle returns Party Manager Create individuals and groups, manage roles. Web tools Track site traffic and related performance metrics. Application Work Effort Events, calendar, project management, and more ready to be customized Manager to meet your specific needs.1.3.4 Different Open Source ERP Software’sEnterprise Resource Planning (ERP) is most crucial for a business and they really help businessto streamline multisite environment with unified processes across locations. There are so manyDepartment of industrial engineering and management Page 10
  11. 11. R.V. College of Engineeringproprietary and commercial ERP solutions available like, SAP, Microsoft Dynamics, Oracle e-Business etc. But, very few know that there is a plethora of Free or Low Cost Open Sourcesolutions that are extremely competent as well as with proper customer support just like theproprietary ones. Here is a list of 12 such Open Source ERP/CRM solutions that are either crossplatform or browser/web based so that the solutions run on any platforms. All of them have Freeversions available without support and some of them offer paid support as optional. a. Compiere: Compiere is a Comprehensive, Adaptable and Low Cost ERP (Java based) solution. Over 1.35 million downloads indicate the proven ERP package. Compiere has support for Cloud Infrastructure, Integration with Sales force and much more. Automate all your business services functions, improve efficiency and customer satisfaction, easy quick customizations, high quality but with low cost ERP suit that will give other competitors a run. b. PostBooks: PostBooks is a full-featured, fully-integrated accounting, ERP, and CRM system, based on the award winning xTuple ERP Suite. Built with the open source PostgreSQL database and the open source Qt framework for C++, it provides the ultimate in power and flexibility for a range of businesses and industries. c. Open taps: Open taps is a full-featured ERP and CRM suite which incorporates several open source projects, including Apache Geronimo, Tomcat, and OFBiz for the data model and transaction framework; Pentaho and Jasper Reports for business intelligence; Funambol for mobile device and Outlook integration; and the Open taps applications which provide user-driven applications for CRM, accounting and finance, warehouse and manufacturing, and purchasing and supply chain management. d. Adempiere: A Java based ERP-System which started as a fork of Compiere, supports a lot of features. A fully fledged ERP, CRM and Supply chain management, Point of Sale suit. e. WebERP: webERP is a complete web based accounting/ERP system that requires only a web-browser and pdf reader to use. It has a wide range of features suitable for many businesses particularly distributed businesses in wholesale and distribution. It is developed as an open-source application and is available as a free download to use. The feature set is continually expanding as new businesses and developers adopt it.Department of industrial engineering and management Page 11
  12. 12. R.V. College of Engineering f. BlueERP: BlueERP is a double entry accounting application for small and medium business. Written in PHP, it is delivered through a LAMP environment to provide web access to your accounts. g. Dolibarr: Dolibarr is an ERP/CRM for small and medium companies but also independent or foundations. Dolibarr success is probably due to the 3 simple rules applied on project since the beginning: Easy to install, Easy to use, Easy to develop. Supports lot of features like Supply chain management, proposal management, order management, payment management and much more. h. ERP5: A full featured high end open source ERP designed for better business process, collaboration and leaner management. i. JFire: JFire is a new, powerful and free ERP, CRM, eBusiness and SCM /SRM solution for business enterprises. JFire is entirely free/open-source software, uses the latest Java technologies (EJB 3, JDO 2, Eclipse RCP 3.3) and is designed to be highly customizable. It is a complete and extensible solution that fulfills all your business needs like user management, online trade with business partners, points of sale, various distribution channels forming a distribution network, store management etc. j. OpenERP: OpenERP is open source ERP suit that supports Enterprise modules, Logistics, Accounting and Finance, HRM, CRM, Project Management, Business Process and more. It is complete package with commercial version available. k. Apache OFBiz: The Apache Open for Business Project is an open source enterprise automation software project licensed under the Apache License Version 2.0. As per OFBiz, Open Source enterprise automation means: Open Source ERP, Open Source CRM, Open Source E-Business / E-Commerce, Open Source SCM, Open Source MRP, Open Source CMMS/EAM, and so on. l. OpenBravo: OpenBravo is a web based ERP solution originally was based on Compeiere which is also Open Source. It supports standard ERP features like production information, inventory, customer information, order tracking, and workflow information.Department of industrial engineering and management Page 12
  13. 13. R.V. College of Engineering1.4. Literature ReviewParijat Upadhyay et al. made an effort to explore and elaborate the issues in the implementationand reliability of ERP software small and medium scale enterprise (SMEs) with the help ofPareto Analysis since the functionality used at SMEs is not the same as in large scales, hencesacrificing the modules is the secret behind successful implementation of ERP and hence thereliability. [1]Poonam Garg et.al. explains the reasons for failure in implementation of ERP packages in IndianRetail Organizations. The major roadblocks in the implementation of ERP are inadequateresources and poor involvement of end user. ERP is more of a people project then an IT projectwhich cannot be reliably implemented unless there is proper involvement and input by the enduser. [2]Mark C. Van Pul et.al. have provided a general overview of theories and processes that isfollowed to check the reliabilities of a software package. With the help of intensive case studiesand mathematical formulas of reliability, it comprehends the fact that no software is completeand even a zillion dollar satellite has bugs. [3]Krešimir Fertalj et al. presented the optimal selection of input parameters that should be done inSoftware Reliability Growth Model (SRGM). In this particular paper, Weibull model is used totest the reliability of existing installed ERP software and for its further modification. The studyelaborates the steps that should be taken by an end user to check the reliability and to predict thetrend of the ERP product during its usage. Measurement based analysis represents a goodfoundation for the future work in modelling of ERP software. [4]F. Urem et.al. attempted to model the probability of bugs in the ERP software after completelyupgrading it. The method used is Weibull probability density function (PDF). The up gradationof ERP software, which is a necessity, evolves the complexity of the software and hence inducesprobability of increasing the bugs unless regular work is done to reduce and maintain it. [5]Department of industrial engineering and management Page 13
  14. 14. R.V. College of EngineeringChin-Yu Huang et al. studied the testing effort and the efficience on the modeling of softwarereliability. The cost of optimal release of the software was another area studied by the author.Testing efficience and the efforts made in testing were the presentation made by the author. [6]Kristine B. Walhovd studied about the sample on which reliability testing for ERP measureswere performed comprised of age groups from 21 years to 92 years. The amplitude measureswere more reliable at all electrodes as compared to latency measures. The test was done bydividing young and adult age groups into T1 and T2 with a separation of 12-14 months. [7]Sally Wright et al. revealed an understanding of the risks of enterprise resource planningsystems (ERP) for consideration in providing information systems assurance services. Increase inthe potential for control weaknesses and resulting financial statement errors, inaccurate internalinformation due to reengineering techniques and customization efforts are explored in the abovestudies. [8]Yoshinobu Tamura et al. created a fusion of neutral network and software reliability growthmodel. The author has presented new approach of software reliability growth model. Numerouscases and examples have been quoted to analyze the actual fault count. Then, for open sourcesoftware the efficiency have been considered in the mention paper. [9]Wangbong Lee et al. They presented as an approach to software reliability assessment of OSSadopted software system in the early stage. It shows the inadequacy of the conventionalreliability models to test the reliability of an OSS (Open source software) as OSS can bemodified but the COTS (Commercial off The-Shelf) cannot. [10]Swapna S. Gokhale et al. A conventional approach followed in the reliability testing of softwareis Black Box in which a system is considered as a whole. It is modulated on the basis ofinteraction with outside world which seems to neglect the inner structure, predicting thereliability of a software system based on its architecture, and the failure behavior of itscomponents, is thus essential. This paper proposes a unifying framework for state-based modelsfor architecture-based software reliability prediction. [11]Department of industrial engineering and management Page 14
  15. 15. R.V. College of EngineeringXiaolin Teng et al. The authors have presented a new methodology for predicting softwarereliability in the field environment. Their work differs from some existing models that assume aconstant failure detection rate for software testing and field operation environments, as this newmethodology considers the random environmental effects on software reliability. This newmethodology provides a viable way to model the user environments, and further makesadjustments to the reliability prediction for similar software products. Based on the generalizedsoftware reliability model, further work may include the development of software cost modelsand the optimum software release policies under random field environments. [12] Table 1.2: Benchmark Reliability Models Models Proposed by Year TypeJ-M-Model[19] Z. Jelinski Paul and B. Moranda 1972 BinomialG-O-Model[18] Amrit Goel and Kazu Okumoto 1979 PoissonExecution Time Model[20] John Musa 1975Hyper Exponential Model[21] Ohba 1984Weibull Model[22] Weibull 1983 BinomialS-Shape Model[23] S. Yamada, M. Ohba, and S.Osaki 1983 GammaDuane Model[18] J.T Duane 1964Geometric Model[24] Paul B. Moranda 1979 BinomialLogarithmic Poisson Model[25] Musa –Okumoto 1984 PoissonLV Reliability Growth Model[26] A. Ghaly, P. Chan, & B. Littlewood 1986 Gamma1.5 Problem GenesisThere is currently a need for a creditable end-to-end software reliability model that can bedirectly linked to reliability prediction from the very beginning (i.e. software design), so as toestablish a systematic SRE procedure that can be certified, generalized and refined. The cost ofcorrecting a software error generally increases by magnitudes for every phase of the life cycle.Ideally most of the errors are detected by the end of the unit testing phase. Ideally, the errorsfound during the integration phase are those due to interfaces that could not have been easily orpossibly found during previous phases. Ideally the number of errors detected levels off by theacceptance test phase. If it is known what the average cost of fixing a bug is during each phase ofthe life cycle, it can be estimated what the cost of repair is and also what it could be. If theDepartment of industrial engineering and management Page 15
  16. 16. R.V. College of Engineeringaverage cost is not known, then the relative cost may be found by comparing real errors detectedover time against the ideal. Although, there has been an extensive research work being conductedin the area of software reliability, but there is extremely less work being focused on open sourcesoftware, especially of Enterprise Resource Planning type, which the current business has highdemands. According literature survey many of the previous works on software reliability haveused secondary data source for carrying out their research. There is lot of scope for researchers touse primary data source and conduct reliability analysis on open source Enterprise resourceplanning software. Hence, this poses a high research gap in the area of open source ERPapplications in terms of software reliability.1.6 Objectives  To study on open source ERP software package and understand various business processes.  To study different parameters that affects the reliability of an open source ERP software.  To perform black box testing and identify bugs in open source ERP software packages.  To improve precision of estimation of software architect reliability of ERP system of manufacturing.Department of industrial engineering and management Page 16
  17. 17. R.V. College of Engineering 2.0 THEORETICAL CONCEPTS AND FUNDAMENTALSThe Institute of Electrical and Electronic Engineers (IEEE) defines software reliability as theprobability that software will not cause a system failure for a specified time under specifiedconditions. The probability is a function of the existence of faults in the software. The inputs tothe system determine whether existing faults, if any, are encountered. John Musa of AT&T BellLaboratories defines software reliability as the probability that a given software system operatesfor some time period without software error, on the machine for which it was designed, giventhat it is used within design limits. The measurement and analysis techniques include softwaremetrics, software reliability models, and software analyses such as fault trees and failure modeseffects and critically (FMECA). Software metrics are measures of some aspect of the softwareproduct or process itself. Software reliability models, for the most part, model the failuresoccurring because of the software. Software analysis enables development personnel to finderrors in the software while the software is still in a laboratory environment.There are at least four major reasons why reliable software has become a very important issue inthe last decade or so. 1. Systems are becoming software intensive. Mainly flight systems are becoming more software intensive than hardware intensive. Financial systems including teller, automated teller, and loan processing are software intensive. Defense and energy systems are becoming more software intensive. Everything from insurance rates to credit histories to hotel reservations to long-distance telephone calls is performed by software. Software affects our daily lives. 2. Many software-intensive systems are safety critical. Flight systems, electronic warfare systems, radar, air traffic control, medical systems, energy systems, and space systems are all software-intensive systems that are also safety critical. Even systems that are not safety critical may be mission critical, meaning that success is critical to some end purpose (such as defeating an enemy at war), or failure is extremely costly financially. 3. Customers are requiring more reliable software. Many government contracts are now requiring that an established level of software reliability be achieved. Software has also become part of the system reliability allocations on many government contracts. Commercial clients are also requiring more reliable systems, and many are attempting toDepartment of industrial engineering and management Page 17
  18. 18. R.V. College of Engineering establish the same criteria as the government for developing of reliable software. At one time, software reliability was assumed to be 1 for purposes of determining system reliability. Those days are behind us. 4. Software errors are not being tolerated by end users or by clients of end users. Financial institutions, medical institutions, the government, communication corporations, and other corporations are in a position of being legally liable for software that is not accurate, that causes potential loss of life or loss of mission, that causes inconvenience to end users, and that causes end users to lose profits. In addition to being liable, users and developers of software are also facing increasing maintenance costs. 5. The cost of developing software is increasing. Data from a variety of sources show that for many systems developing the software is becoming one of the major costs of the system, if not the major cost. Much of the software cost can be associated with corrective action, particularly corrective action late in the development cycle. The cost of maintaining software has been shown in some studies to be as much as 40-70% of the total development cost. Some NASA and Air Forces have estimated it to be 50% of their development cost.2.1 Software Reliability ModelingA software reliability model specifies the general form of the dependence of the failure processon the principal factors that affect it: fault introduction, fault removal, and the operationalenvironment. These models are used to predict how much more time the software needs to betested to achieve the desired failure intensity and to predict the expected reliability of thedelivered software. The model parameters may be determined by means of the following:(1) Estimation: measures the reliability by applying statistical inferences to the collected failuredata. This method validates the goodness of the model by assessing its current reliability.(2) Prediction: measures the future software reliability using the available software metrics.The failure data that is used in the reliability models may be of two types:(1) Failure count data which is expressed as the number of failures in each time interval.(2) Time between failure data which is expressed as the time interval between consecutivefailures.One type of input data can be transformed to the other to the alternate models either by using thecumulative failure data or by using some of the existing reliability tools such as CASRE andDepartment of industrial engineering and management Page 18
  19. 19. R.V. College of EngineeringSMERFS. A well defined software reliability model can determine important characteristics ofthe failure process by incorporating expressions for the average number of failures experiencedat any point in time, the average number of failures in a time interval, the failure intensity at anypoint in time, and the probability distribution of failure intervals. A good software reliabilitymodel, based on sound assumptions, gives better projection of future failure behavior, computesuseful quantities, is simple, and is widely applicable.2.2 Software Reliability Model ClassificationOne of the early reliability models, which was based on hardware reliability concepts, wasdeveloped by Duane. In the seventies, many software reliability models were proposed,developed and widely used. Since then, many different software reliability models have beendeveloped and numerous researchers in software reliability engineering have attempted tocategorize and classify them. Classify the reliability models in terms of five attributes:(1)Time domain: either calendar or execution time.(2)Category: either finite or infinite number of failures. For the finite number of failures categorymodels, there are a number of classes depending on the functional form of the failure intensity interms of time. For infinite failure category models, there are a number of families depending onthe functional form of the failure intensity in term of the expected number of failuresexperienced.(3) Type: the distribution of the number of failures experienced as a function of t.(4) Class: functional form of the failure intensity expressed in terms of time (for finite failurecategory only).(5) Family: functional form of the failure intensity expressed in terms of the expected number offailures experienced (for infinte failure category only).For the sake of simplicity, first separate the finite from the infinite models. Then they incorporatethe five attributes as a guide to finding the relationship between the models; thus clarifying thecomparison between the models. The simplicity of this classification explains its popularity ofusage. Two main categories of software reliability models:(1) software growth reliability models that estimate reliability using the error history.(2) statistical models that estimate the reliability using the results (success or failure) ofexecuting test cases.Department of industrial engineering and management Page 19
  20. 20. R.V. College of EngineeringThe software growth reliability models are classified based on the nature of the failures. The timebetween failures models, failure counts models, and fault seeding and input domain basedmodels. Categorize models into two major types:(1) Type I : time between successive failures models, which breaks down to failure rate Type I-1and random function Type I-2.(2) Type II : the number of failures up to a given time.Classify reliability models as follows:(1) Data-domain models: A better reliability estimate can be achieved if all of the combinationsof the inputs are identified and the outcomes are well observed. To implement this theory, thismodel category is decomposed into fault-seeding models and input-domain models. (2) Time-domain models: model the failure process using the failure history to estimate the number offaults and the required test time to uncover these faults. Homogeneous Markov, non-homogeneous Markov, semi-Markov are models that belong to the time-domain model. Classifysoftware reliability according to software development life cycle phases. Their classification iswell defined and comprehensive. Table 2.1. Software Reliability Growth Model Examples Model Model μ(t) Reference Comments Name Type Goel-Oku Concave a(l-e-bt) Goel,79 Also called Musa model or moto (G-O) a  0, b>O exponential model G-OS- S-Shaped a( 1-(1+bt)e-bt) Yamada,83 Modification of G-O model to Shaped a  0, b>O make it S-shaped (Gamma function instead of exponential) Hossain- Concave a( l-e-bt)/(1+ce-bt) Hossain,93 Solves a technical condition Dahiya/G- a  0, b>O, c>0 with the G-O model. Becomes O same as G-O as c approaches O. Gompertz S-Shaped a(bct) Kececioglu,, Used by Fujitsu, Numazu a  0, 0  b  1, 0<c<1 91 Works Pareto Concave a(l-(l+t/  )l-  Littlewood, Assumes failures have 81 different failure rates andDepartment of industrial engineering and management Page 20
  21. 21. R.V. College of Engineering a  0,  >0, 0    1 failures with highest rates removed first Weibull Concave a(l-e-btC) Musa,87 Same as G-O for c=1 a  0, b>0,c>0 Yamada Concave a(1-e-r  (1-e-  t)) Yamada,86 Attempts to account for testing Exponential a  0, r  >0,  >0 effort Yamada S-Shaped (  t 2 / 2 ) Yamada,86 Attempts to account for testing a(1  e  r (1e ) ) Raleigh effort Log Infinite (l/c)ln(c  t+l) Musa,87 Failure rate decreases but does Poisson Failure c>O,  >O not approach 02.3 Theoretical Comparison of TechniquesThis section compares the three parameter estimation techniques from a theoretical perspective.We focus on their ease of use, confidence interval shape, and parameter scalability. Sinceoptimization packages are readily available, maximum likelihood, classical least squares, andalternative least squares are all straightforward to solve. However, maximum likelihood onlyapplies to the G-O model, and a new maximum likelihood equation must be derived for eachsoftware reliability growth model. These equations can be difficult to derive, especially for themore complex models. Classical least squares applies to the exponential family of models thatincludes the G-O model. It is fairly easy to modify this equation for similar models. Alternativeleast squares are the easiest to use since it applies to any software reliability growth model, so thealternative least squares method is the easiest to apply. Confidence intervals for all of theestimation techniques are based on assuming that estimation errors are normally distributed. Forthe maximum likelihood technique, this assumption is good for large sample sizes because of theasymptotically normal properties of this estimator. However, it is not as good for the smallersamples that we typically have. Nevertheless, the maximum likelihood technique provides thebest confidence intervals because it requires less normality assumptions and because it providesasymmetric confidence intervals for the total defect parameter. The lower confidence limit islarger than the number of experienced defects, and the upper confidence limit is farther from thepoint estimate than the lower confidence limit to represent the possibility that there could bemany defects that have gone undetected by testing. Conversely, for the least squares techniques,the lower confidence limit can be less than the number of experienced defects (which isDepartment of industrial engineering and management Page 21
  22. 22. R.V. College of Engineeringobviously impossible), and the confidence interval is symmetric. Also, additional assumptionspertaining to the normality of the parameters are necessary to derive confidence intervals for theleast squares techniques. The transformation technique consists of multiplying the test time by anarbitrary (but convenient) constant and multiplying the number of defects observed by a differentarbitrary constant. For this technique to work, the predicted number of total defects must beunaffected by the test time scaling and must scale the same amount as the defect data. Forexample, we may experience 50 total defects during test and want to scale that to 100 forconfidentiality or ease of reporting. To do that transformation, the number of defects reportedeach week must be multiplied by 2. If 75 total defects were predicted by a model based on the unscaled data, then the total defects predicted from the scaled data should be 150.Reliability growth models are categorized as hardware models and software models. Hardware models – using for electronics systems, functions blocks, electronics components without connections to software. Basic terms are a reliability operating state and a failure. There are two basic types of failures during the development phase – random failures, early failures. Software models –using for software. Probabilistic reliability growth models – because of no unknown parameters associated with these models, the data obtained during the program cannot be incorporated. Statistical reliability growth models – unknown parameters are associated with these models. In addition, these parameters are estimated throughout the development of the product in question. Time independent reliability growth models – number of failures or repairs in definite time interval are not depended on time. Time dependent reliability growth models – a reliability growth model is function of time. Continuous reliability growth models – these are time models. Discrete reliability growth models – these are useful for unrecoverable objects, there are two discrete states – a reliability operating state or a failure. Classically reliability growth models – mathematical equipment is theory of probability, Duane reliability growth model and its modifications – these are continuous, time dependent and statistical models,Department of industrial engineering and management Page 22
  23. 23. R.V. College of Engineering Stochastic reliability growth models – a reliability growth is non-stationary stochastic process – non-stationary stochastic Poisson process. Bayes and quasi-Bayes reliability growth models Unconventional reliability growth models – there are all reliability growth models, for which is no existing possibility to arrange in classification categories.2.4. Exponential ModelsAll software reliability models of the exponential class have a common set of assumptions. Inaddition to these common assumptions, each model has its own unique set of assumptions. Thestandard assumptions are (Lyu 1995): The software is operated in a similar manner as that forwhich reliability predictions are to be made. This assumption is to ensure that the data collectedin that particular environment is applicable to the environment in which the reliabilityprojections are to be made. Every fault has the same chance of being encountered and is of thesame severity as any other faults. This assumption is to ensure that the various failures all havethe same distributional properties. One severity class might have different failure rates whichmay require separate reliability analysis. The failures are independent. A failure occurs when thefaults are encountered, so having independent failures simplifies the maximum likelihoodestimates. Exponential class models have two major types: binomial-type and Poisson-type. Inaddition to the common assumptions for the exponential class models, the binomial-type modelsassume that the failures are removed from the software as soon as they occur and introduce nomore faults during the fix. The Poisson-type models assume that the faults remaining in thesoftware is a Poisson random variable. The principal difference between the binomial andPoisson type models is how the remaining number of faults are treated. Considering equations(3) and (4), binomial- type models treat the number of remaining faults as a fixed number. Whilein the Poisson-type models, the number of remaining faults is treated as random variable (Musa,Iannino, Okumoto 1987). Jelinski-Moranda, Musa and Schneidewind models are some thedifferent reliability models. Table 1 summaries the reliability functions for these models.Department of industrial engineering and management Page 23
  24. 24. R.V. College of Engineering Table 2.2: Summary of reliability functions for Jelinski-Moranda, Musa and schn. Models Reliability Jelinski-Moranda Musa’a Model Schneidewind’s Functions Model Model F(t) 1  e t 1 e  1t   /   1  e  t  f(t) e t 1e  t e t z(t)  1 e  t 1   /    e  t  1  (t )  N 1  e t   0 1  e   1t   /   1  e  t   (t ) N e t  0 1e   1t e  tDepartment of industrial engineering and management Page 24
  25. 25. R.V. College of Engineering 3.0 METHODOLOGYThe following methodology is used to identify error data in the Ofbiz ERP software package.The data collection process is the most critical prerequisites to measuring software reliability.The effectiveness of any reliability measurement will be directly related to the effectiveness ofcollecting the data necessary for measurement.  Study of Ofbiz ERP software package.  Develop operational profile.  Testing  Data analysis3.1 Study of Ofbiz ERP software package.The first step in methodology is to thoroughly understand various business processes existing inOfbiz ERP software package. It is very much essential to understand various business processesbefore the testing of the software. They are various modules available in Ofbiz software such ascatalog manager, bill of materials, purchase module, sales module etc. Key is to understand theintegration of all modules.3.2 Develop operational profileAn Operational Profile is simply the set of Operations and their probabilities of occurrence. Mostfrequently used modules are given more emphasis. More Test cases have to be generated forthose modules which are frequently used. In this work the modules which are identified arecatalog manager, bill of materials, purchase module and sales module.3.3 TestingSoftware testing is an important technique for assessing the quality of software product. Twobasic software testing methods are Black Box testing and White Box testing. In this work thesoftware is tested using black box testing. Black Box testing includes performance testing andfunctionality testing.3.3.1 Performance testing on different operating systemsThe performance test is carried to identify how this Ofbiz ERP software package operates ondifferent operating systems such as Windows XP, Windows Vista, Windows 7, Ubuntu.Department of industrial engineering and management Page 25
  26. 26. R.V. College of Engineering Table 3.1: Evaluations of Ofbiz in OSName of Evaluation Evaluation of OFBiz On OSObject of Evaluation OFBiz running on OS on 3GB RAMTest Case Used Execution of OFBiz in 64 bit OS a. Windows XP b. Windows Vista c. Windows 7 Home Basic d. UbuntuActual Output In Execution of OFBiz in bit 64Windows professional OS a. The performance is better compared to previous version. But optimum performance varies if RAM is enhanced. b. Performance is much better w.r.t installation, navigation, configuration c. Same as previous versions of Windows. d. Performance is much better compared to windowsRemarks Successful performance in windows XP , Vista, 7 and Ubuntu3.3.2 Performance testing on different web browsers.After testing the performance of software on different operating systems next step is to test Ofbizsoftware performance on different web browsers. Mozilla Firefox, Internet Explorer and GoogleChrome are identified browsers for testing.Department of industrial engineering and management Page 26
  27. 27. R.V. College of Engineering Table 3.2: Ofbiz performance for Browser Name of Testing OFBiz Testing OFBiz Testing OFBiz Evaluation performance on Mozilla performance on Internet performance on Google Firefox version 13.0 Explorer 9 Chrome Object of Firefox performance with IE-9.0 performance with Google Chrome Evaluation OFBiz OFBiz performance with OFBiz Test Case 1. Navigation of 5. Navigation of 9. Navigation of Used pages pages pages 2. Cookies 6. Cookies Clearance 10. Cookies Clearance Clearance 7. History Scrutiny 11. History Scrutiny 3. History Scrutiny 8. Page Visualization 12. Page Visualization 4. Page Visualization Actual 1. Navigation of 5. Navigation of 9. Navigation of Output Pages are very Pages are very pages are quite smooth smooth faster 2. Proper cookie 6. Cookies are not 10. In Google chrome, management managed properly incognito window 3. Proper history and 7. No proper history enables the better cache and cache cookies clearance. management management 11. Better history 4. The pages are 8. The pages are management due visually better to visually not so to incognito experience better to window. experience as user 12. The pages visualization is better compare to internet explorer 9 Remarks Mozilla Firefox seems to IE-9.0 seems not to be best Google chrome is also be best compatible with compatible with OFBiz found to be best OFBiz compatible browser after Firefox Mozilla.Department of industrial engineering and management Page 27
  28. 28. R.V. College of Engineering3.4 Data collectionSoftware testing is an important technique for assessing the quality of software product. Twobasic software testing are Black Box testing and White Box testing. Black Box testing includesperformance testing and functionality testing. In performance testing, data is collected on basisof working of modules in different browsers in single operating system and also in differentoperating system.From the study found that software failure follows exponential distribution, for example supposewe test to failure a large number of software operation, for each small unit of time, if wecalculate the failure rate and plot the same against time t, the resulting graph is the failure ratecurve. The value of reliability R(t) is 1 at t = 0 and it decreases continuously with time when (t) is large, all the software will have failed giving R(t) = 0 at t ∞ It can be proved that in case of constant failure rate, R= λ = constant failure rate T = mission time. We conducted experiment on oFbiz open source softwarecreating bill of material ,purchase order, sales order and purchase order through MRP run aresome of certain operations which has been frequently used in many organizations. By creatingbill of material and time is noted down, these has been repeated for ten times and tabulated,average time of ten reading have calculated and standard time has been found, standard time issum of average time and 10% of average time. Then based on standard time failure rate (λ) iscalculated, failure rate is number of time creating a bill of material exceeded standard time, sameDepartment of industrial engineering and management Page 28
  29. 29. R.V. College of Engineeringprocedure is been carried to other ERP modules and then the reliability of software in particularweb browser for particular operating system is calculated.Standard time = Basic average time + (10%* Basic average time)Failure rate (λ) = No. Of operations exceeds standard time/total no. of trails3.4.1 Performance testing of different modules of Ofbiz on different Webbrowsers.The important modules which are identified in operational profile stage are being tested ondifferent web browsers. Time taken to create bill of materials, purchase order, sales order andpurchase order through MRP are noted down for different web browsers.Readings of 10 trails for different browsers with different operating system for processing timeof different operations shown in below tables :- Table 3.3: Windows XP –Internet Explorer Purchase order Bill of Purchase Sales through Sl.no material order order MRP 1 9.3 4.2 4.2 5.6 2 9 4.1 4 5.4 3 8.9 3.8 3.8 5.1 4 8.4 3.7 3.5 4.9 5 8.2 3.5 3.4 4.6 6 8.1 3.4 3.1 4.4 7 7.9 3.2 2.8 4.2 8 7.8 2.9 2.7 4 9 7.7 2.6 2.3 3.9 10 7.7 2.6 2.2 3.9 sum 83 34 32 46 Avg 8.3 3.4 3.2 4.6 Note all readings are in minutesDepartment of industrial engineering and management Page 29
  30. 30. R.V. College of Engineering Table 3.4: Windows XP –Mozilla Firefox Purchase order Bill of Purchase Sales through Sl.no material order order MRP 1 9.3 4.3 4.3 5.6 2 9 4.2 4.1 5.4 3 8.9 3.9 3.9 5.1 4 8.4 3.8 3.6 4.9 5 8.2 3.6 3.5 4.6 6 8.1 3.5 3.2 4.4 7 7.9 3.3 2.9 4.2 8 7.8 3 2.8 4 9 7.7 2.7 2.4 3.9 10 7.7 2.7 2.3 3.9 sum 83 35 33 46 Avg 8.3 3.5 3.3 4.6 Note all readings are in minutes. Table 3.5: Windows XP –Google Chrome Purchase order Bill of Purchase Sales through Sl.no material order order MRP 1 9.2 4.3 4.3 5.5 2 8.9 4.2 4.1 5.3 3 8.8 3.9 3.9 5 4 8.3 3.8 3.6 4.8 5 8.1 3.6 3.5 4.5 6 8 3.5 3.2 4.3 7 7.8 3.3 2.9 4.1 8 7.7 3 2.8 3.9 9 7.6 2.7 2.4 3.8 10 7.6 2.7 2.3 3.8 sum 82 35 33 45 Avg 8.2 3.5 3.3 4.5 Note all readings are in minutes.Department of industrial engineering and management Page 30
  31. 31. R.V. College of Engineering Table 3.6: Windows Vista – Internet Explorer Purchase order Bill of Purchase Sales through Sl.no material order order MRP 1 9.3 4 4.5 5.7 2 9 3.9 4.3 5.6 3 8.7 3.6 4.1 5.4 4 8.6 3.5 3.8 5.1 5 8.5 3.3 3.7 4.8 6 8.3 3.2 3.4 4.6 7 8.2 3 3.1 4.4 8 8.2 2.7 3 4.2 9 8.1 2.4 2.6 4.1 10 8.1 2.4 2.5 4.1 sum 85 32 35 48 Avg 8.5 3.2 3.5 4.8 Note all readings are in minutes. Table3.7: Windows Vista –Mozilla Firefox Purchase Bill of Purchase Sales order through Sl.no material order order MRP 1 9.6 4.2 4.6 6 2 9.4 4.1 4.4 5.9 3 9.2 3.8 4.2 5.7 4 8.9 3.7 3.9 5.4 5 8.6 3.5 3.8 5.1 6 8.5 3.4 3.5 4.9 7 8.3 3.2 3.2 4.7 8 8.2 2.9 3.1 4.5 9 8.1 2.6 2.7 4.4 10 8.2 2.6 2.6 4.4 sum 87 34 36 51 Avg 8.7 3.4 3.6 5.1 Note all readings are in minutes.Department of industrial engineering and management Page 31
  32. 32. R.V. College of Engineering Table 3.8: Windows Vista –Google Chrome Purchase Purchase Sales order through Sl.no Bill of material order order MRP 1 9.6 4.3 4.3 5.9 2 9.3 4.2 4.1 5.8 3 9.2 3.9 3.9 5.6 4 8.7 3.8 3.6 5.2 5 8.5 3.6 3.5 5.1 6 8.4 3.5 3.2 4.8 7 8.2 3.3 2.9 4.7 8 8.1 3 2.8 4.3 9 8 2.7 2.4 4.3 10 8 2.7 2.3 4.3 sum 86 35 33 50 Avg 8.6 3.5 3.3 5 Note all readings are in minutes. Table 3.9: Windows 7 – Google Chrome. Purchase order Purchase Sales through Sl.no Bill of material order order MRP 1 9.5 3.8 4.2 5.1 2 9.2 3.7 4 4.8 3 9.1 3.4 3.8 4.7 4 8.6 3.3 3.5 4.6 5 8.4 3.1 3.4 4.4 6 8.3 3 3.1 4.2 7 8.1 2.8 2.8 3.7 8 8 2.5 2.7 3.6 9 7.9 2.2 2.3 3.5 10 7.9 2.2 2.2 3.4 sum 85 30 32 42 Avg 8.5 3 3.2 4.2 Note all readings are in minutes.Department of industrial engineering and management Page 32
  33. 33. R.V. College of Engineering Table 3.10: Windows 7 – Mozilla Firefox Purchase order Purchase Sales through Sl.no Bill of material order order MRP 1 8.9 4.3 4.7 5.4 2 8.7 4.2 4.5 5.1 3 8.6 3.9 4.3 5 4 8.1 3.8 4 4.9 5 7.9 3.6 3.9 4.7 6 7.8 3.5 3.6 4.5 7 7.6 3.3 3.3 4 8 7.5 3 3.2 3.9 9 7.5 2.7 2.8 3.8 10 7.4 2.7 2.7 3.7 sum 80 35 37 45 Avg 8 3.5 3.7 4.5 Note all readings are in minutes. Table 3.11: Windows 7 – Internet Explorer Purchase order Purchase Sales through Sl.no Bill of material order order MRP 1 8.5 3.3 3.6 4.3 2 8.3 3.2 3.4 3.8 3 8.3 2.9 3.2 3.7 4 7.7 2.8 2.9 3.6 5 7.5 2.6 2.8 3.4 6 7.4 2.5 2.5 3.3 7 7.2 2.3 2.2 2.7 8 7.1 2 2.1 2.5 9 7.1 1.7 1.7 2.4 10 6.9 1.7 1.6 2.3 sum 76 25 26 32 Avg 7.6 2.5 2.6 3.2 Note all readings are in minutes.Department of industrial engineering and management Page 33
  34. 34. R.V. College of Engineering Table 3.12: Ubuntu– Internet Explorer Firefox Bill of Sl.no material Sales order Purchase Order 1 8.2 3.2 3.2 2 8.1 3 3.1 3 8 2.9 2.9 4 7.6 2.7 2.5 5 7.4 2.6 2.5 6 7.2 2.5 2.3 7 7.1 2.1 2.2 8 7 1.9 1.9 9 6.8 1.7 1.7 10 6.6 1.4 1.7 Sum 74 24 24 Avg 7.4 2.4 2.4 Note all readings are in minutes. Table 3.13:Ubutu– Internet Explorer Firefox Bill of Sales Purchase Sl.no material order Order 1 8.4 4 3.9 2 8.3 3.8 3.8 3 8.2 3.7 3.6 4 7.8 3.5 3.2 5 7.6 3.4 3.2 6 7.4 3.3 3 7 7.3 2.9 2.9 8 7.2 2.7 2.6 9 7 2.5 2.4 10 6.8 2.2 2.4 Sum 76 32 31 Avg 7.6 3.2 3.1 Note all readings are in minutes.Department of industrial engineering and management Page 34
  35. 35. R.V. College of Engineering Table 3.14 : Ubuntu– Internet Explorer Firefox Bill of Sales Sl.no material order Purchase Order 1 8.3 3.7 3.7 2 8.2 3.5 3.6 3 8.1 3.4 3.4 4 7.7 3.2 3 5 7.5 3.1 3 6 7.3 3 2.8 7 7.2 2.6 2.7 8 7.1 2.4 2.4 9 6.9 2.2 2.2 10 6.7 1.9 2.2 Sum 75 29 29 Avg 7.5 2.9 2.9 Note all readings are in minutes.3.4.2 Functionality TestingFunctional testing is a type of black box testing that bases its test cases on the specifications ofthe software component under test. Functions are tested by feeding them input and examining theoutput, and internal program structure is rarely considered.Functional testing differs from system testing in that functional testing " a program by checkingit against design document or specification", while system testing " a program by checking itagainst the published user or system requirements"Functional testing typically involves five steps:- 1. The identification of functions that the software is expected to perform 2. The creation of input data based on the functions specifications 3. The determination of output based on the functions specifications 4. The execution of the test case 5. The comparison of actual and expected outputsDepartment of industrial engineering and management Page 35
  36. 36. R.V. College of Engineering3.4.2.1 TEST CASES Table 3.15: Test cases Step. Step Description Test Data Actions Expected Actual Status no Results Result T01 Examine entering Business Click on Loged-in Loged-in Pass username & 12345 Login password T02 Examine entering Business Click on Pop-up box Pop-up box Pass correct username 12366 Login & wrong password T03 Examine entering Business Click on Pop-up box Pop-up box Pass wrong username 12345 Login & correct password T04 Examine entering Business Click on Pop-up box Pop-up box Pass wrong username 12356 Login & wrong password T05 Ensure after log-in Business Click on Open Open Pass should go to 12345 Login homepage homepage homepage T06 Check BOM on Create all Click on BOM pdf BOM pdf Pass screen product BOM give price, simulation supplier and facilities T07 Check BOM on Create Click on Should not Should not Pass screen product BOM show BOM show BOMDepartment of industrial engineering and management Page 36
  37. 37. R.V. College of Engineering Without simulation giving facilities T08 Examine sales Input Click on Should Should give Pass enquiry enquiry supplier give supplier number supplier sales sales T09 Examine product Input Click on Display Display Pass detail product product product product name/ID detail detail detail T10 Examine entering Id: cap Click on Show error Show error Pass same product id & name: cap create that that product name product duplicate duplicate key arise key arise T11 Examine entering Id: cap Click on Product Product Pass different product name: caps create created created id & product name product T12 Edit product detail Product Click on Go to edit Go to edit Pass detail edit screen screen product T13 Examine product Engine Click on Pop-up box Pop-up box Pass ID lathe create product T14 Examine product Engine Click on Product Product Pass ID without space _lathe create created created product T15 Examine product Without Click on Pop-up box Pop-up box Pass without internal internal create name name product T16 Examine product With Click on Pop-up box Pop-up box Pass with internal name internal createDepartment of industrial engineering and management Page 37
  38. 38. R.V. College of Engineering name product T17 Creating suppliers Product Click on Pop-u box Pop-u box Pass for subassemblies id:__ create without product id Product & name name:__ T18 Creating suppliers Product Click on Pop-u box Pop-u box Pass for subassemblies id:chuck9 create with product id & Product name name: chuck T19 Changing Indian Click on Not Not Pass currency in price rupee to edit applicable applicable module USD product price update T20 Creating Select Click on Should Should Pass manufacturing facility has BOM show all show all BOM manufactu simulation elements element ring BOM T21 Creating Select Click on Should Should Pass engineering BOM facility has BOM show only show only engineerin simulation parent parent g BOM element element T22 Examine without Create Click on Pop-up box Pop-up box pass selecting shipping sales or finalize address purchase order order without selecting address T23 Examine selecting Create Click on Sales order Sales order PassDepartment of industrial engineering and management Page 38
  39. 39. R.V. College of Engineering shipping address sales or finalize or purchase or purchase purchase order order is order is order with created created selecting address T24 Examine payment Create Select Should Should Pass mode sales or shipping show the show the purchase address payment payment order with mode mode selecting address T25 Examine payment Create without Should not Should not Pass mode sales or Selecting show the show the purchase shipping payment payment order address mode mode without selecting address3.4.2.2 Ofbiz Defect Tracker1. Problem DescriptionWhile creating sales order through order entry, how shall we ship it? Mode for USPS standardshown calculated offline. This is to be selected but by selecting will not allow us to carry out thesales order. Bug severity:- Minor Found By :- Managing Maniac Date :- 2-4-2012Steps to Reproduce• Go to application-select order manager• Select order entry-give product ID and click on add to orderDepartment of industrial engineering and management Page 39
  40. 40. R.V. College of Engineering• Finalize the order-select the shipping address-shipping mode with USPS standard-paymentmode• Click on continue to finalize order and it should show the order conformation page. Fig.3.1: Quick finalize orderWork AroundSales order is created using order entry in order manager, by selecting any other shipping modeand then click on continue to final order after creating order we can change the shipping mode toUSPS standard by updating the shipping information.2. Problem descriptionWhen a Purchase Order is received manually using the ‘receive functionality’ of FacilityManager module, the invoice entry in accounting is not automatically raised. Bug severity:- Minor Found by :- Managing Maniac Date:- 6-4-2012Department of industrial engineering and management Page 40
  41. 41. R.V. College of Engineering Fig. 3.2: Shows how to receive quick purchase orderSteps to reproduce• Create a purchase order using the order entry screen of Order Manager• Once the order is created, approve the purchase order• In the Facility Manager, select the facility as Kamakshi Palya Plant and receive theinventory using ‘Receive Inventory’ option• Once receive inventory is successful, check the status of the PO in Order Manager. It willbe shown as ‘Complete’• Check for a Purchase Order Invoice entry in accounting module using the functionality‘Find Purchase Invoice’. There should be a PO invoice corresponding to the amount of the POfulfilled.Department of industrial engineering and management Page 41
  42. 42. R.V. College of Engineering Fig.3.3: Finding InvoiceWork Around – When a purchase order is created using the order entry functionality of Ordermanager, there is an option to quick receive purchase order. When a PO is received using thisoption the purchase order invoice entry is made automatically. Shown below is the screenshot ofQuick receive PO functionality.3. Problem descriptionWhen a Purchase Order is raised and approved, in the Quick Receive option, newly createdfacility is not listed. Bug Severity – Minor, data related issue Found by – Managing Maniac Date – 10-4-2012Steps to reproduce –• Create a new facility ‘Kamakshi palya Plant’ of facility type ‘Plant’• During the creation of the PO, in the order entry ship to settings, though the newlycreated plant is listed, there is no option to select it.Department of industrial engineering and management Page 42
  43. 43. R.V. College of Engineering Fig.3.4: Order EntryWork Around-In the Facility Manager, select the facility as Kamakshi Palya Plant and create acontact mechanism of type ‘Postal Address’ and save the details Fig.3.5: Facility ManagerDepartment of industrial engineering and management Page 43
  44. 44. R.V. College of EngineeringTry to create the purchase order again, as you can see in the screenshot below the newly createdplant is visible as an option to be selected for shipment Fig.3. 6: Shipping addresses update4. Problem description – When creating a Purchase Order, in the ‘Add Item’ screen the topmenu bar is not clearly visible as shown in the screenshot below Bug Severity – Low, Cosmetic Found by – Managing Maniac Date – 21-4-2012Steps to reproduce • Create a purchase order using the order entry screen • Select the supplier and click continueDepartment of industrial engineering and management Page 44
  45. 45. R.V. College of Engineering • Enter the order name and order number and click continue • In the add items screen displayed below the text is not clearly visible in top menu Fig.3.7: Screen Visuality Files Modified: ofbiz-trunkapplicationsorderwebappordermgrentryOrderEntryTabBar.ftl Verification: After fixing the defect, it can be seen that the options in top menu bar are clearly visible.Department of industrial engineering and management Page 45
  46. 46. R.V. College of Engineering Fig.3. 8: Screen after solving3.5 Data AnalysisAnalysis of data is a process of inspecting, cleaning, transforming, and modelling data with thegoal of highlighting useful information, suggesting conclusions, and supporting decision making.Data analysis has multiple facets and approaches, encompassing diverse techniques under avariety of names, in different business, science, and social science domains.Data mining is a particular data analysis technique that focuses on modelling and knowledgediscovery for predictive rather than purely descriptive purposes. Business intelligence coversdata analysis that relies heavily on aggregation, focusing on business information. In statisticalapplications, some people divide data analysis into descriptive statistics, exploratory dataanalysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering newfeatures in the data and CDA on confirming or falsifying existing hypotheses. PredictiveDepartment of industrial engineering and management Page 46

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