In our modern society, software has become a very critical component in all kinds of systems and software failures have become the most vital factor that terminates the service and proper function of the whole system. Therefore, it is very important and urgent to understand the software development process and eliminate as many potential problems in software as possible.
Software reliability is defined as the probability of failure-free software operation for a specified period of time in a specified environment.
The determination of software reliability indices is the primary task in the software reliability engineering. The indices are taken as not only the basis for the software reliability design and the constraints during the software development process, but also the foundation of the software’s acceptance.
Software reliability indices are usually divided into Quantitative Indices and Qualitative Indices.
Quantitative indices are quantified software reliability parameters’ values, such as software reliability is quantitatively defined as the probability of failure free operation of a software program for a specified time under specified conditions. However, having a “number”, even with the appropriate accompanying evidence, is not generally sufficient to convince customers or even the system/software suppliers that the software satisfies its requirements. Thus, qualitative indices such as software reliability is also qualitatively defined as a set of attributes that bear on the capability of software to maintain its level of performance under stated conditions for a stated period of time.
A Study method for determining the software reliability qualitative indices based on the two standards of SAE-JA1003 and RTCA D...
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National Institute of Standards and Technology (NIST): Risk Management Guide for Information Technology Systems. Special Publication 800-30, 2002.
The Software Development Life Cycle is seldom used at my place of work. Unfortunately, recent developments in its use are deemed confidential. Due to this fact, this paper will examine in general terms one of the projects we are undertaking right now while at the same time attempting to maintain our confidentiality.
CVSS, or Common Vulnerability Scoring System, provides a method for assessing and prioritizing previously unknown vulnerabilities in an application’s code that have been identified for IT management to address (Scarfone & Mell, 2007). CCSS, or Common Configuration Scoring System, is based off of using similar metrics to CVSS but is focused on known vulnerabilities based upon decisions regarding security configurations of the program.
If given a chance to do things differently, we would first include the additional factors stated above as part of the evaluation criteria of the software providers. Also, as a last step to the process, instead of only relying on the demo by the providers, we would include a ‘pilot project implementation’ stage, where the provider integrates a piece of software to the existing architecture to be used by end users in production on a daily basis. This can provide a real test of usability, compatibility and can be used to evaluate critical measures such as fault tolerance.
I will discuss an implementation of a software quality plan for Irish hospitals through the use of recognised healthcare and software quality models and standards in this essay.
A Computer Software Engineer develops software systems to be used by their clients, such as a website used to sell the client’s products. Although software engineers spend the majority of their time programming and testing the software, a key component to the success of a software engineer is the ability to write a thorough Software Requirement Specification (SRS). A SRS documents the requirements and dependencies needed for the software, prior to beginning any programming. Therefore, a Software Engineer must po The SRS is so important because engineers can have a wide scope of clients that they regularly work with.
Gaining a better understanding of when electronics are about to fail can help engineers and companies be more effective in providing reliable electronics; this will also lead to a greater return on investments for businesses (Seggie, Cavusgil, & Phelan, 2007). Prior attempts of implementing algorithms have all failed due to the large bandwidth required to process the data in real time. The algorithms in this study will not require many resources and will use simple gate-logic and statistical data to alert an end-user of a potential failure. Scores, which are based on inputs from the end-user, for each of the four factors, will serve as the four independent variables for this study: (a) cost, (b) reliability, (c) component replacement, and (d) total system replacement.
The term legacy system has distinct meanings for different individuals. For numerous people, it describes archaic mainframe or dumb-terminal software programs from the 1970s and 1980s (Weber, 2006). To other individuals, it may infer the client/server applications from the 1990s or web applications from the late 1990s (Weber, 2006). The chief point is that each one of these distinct architectures presents different risks that must be thoroughly understood and properly managed (Weber, 2006).
Testing is one of the important methods to boost the confidence of the developers in the reliability of software. Sometimes, programs that are not properly tested perform correct for few months and even years too before some input sets shows the presence of critical errors. Incorrect application that is released to public without fully tested could result in client dissatisfaction and moreover it is important for software in applications that it is free of software faults which might lead to heavy economic loss or even endanger lives. In the past durations, systematic ways to software testing procedures and tools have been developed to avoid many problems. Testing is the most usual technique for fault detection in today’s organization. Main aim of application testing is to boost one's confidence in the correctness of the program being tested.
Flynn, Donal J.; "Information Systems Requirements: Determination and Analysis"; McGraw-Hill Book Company; 1992Parnas; 1985; taken from: Sherer, Susan A.; "Software Failure Risk – Measurement and Management"; Plenum Press; 1992Jones, Carpers; "Patterns of Software Systems Failure and Success"; Thomson computer press; 1996Neumann, Peter G.; "Computer Related Risks"; Addison-Wesley publishing company; 1995Petroski, Henry; "To Engineer is Human"; MacMillan Publishing; 1985Flowers, Stephen; "Software failure: management failure"; Chichester: John Wiley and Sons; 1996.Report of the Inquiry into the London Ambulance Service; February 1993. Simpson, Moira (1994); "999!: My computers stopped breathing !"; The Computer Law and Security Report, 10; March – April; pp 76-81Dr. Dobbs Journal; January 1997 edition<a href="http://catless.ncl.ac.uk/Risks">http://catless.ncl.ac.uk/Risks<a href="http://www.scit.wlv.ac.uk ">http://www.scit.wlv.ac.uk <a href="http://www.bbc.co.uk/news">http://www.bbc.co.uk/news<a href="http://abcnews.go.com/sections/travel">http://abcnews.go.com/sections/travel
Quality is one of the most important components of application development and an integral part of the project process to ensure that errors are not made while
As a result, most of the risk assessment tools that are used today for information systems are measurements of qualitative risk.
In the planning stage, planning for the requirements associated with quality assurance and identifying risks associated with the specific project is also performed. The result of the technical feasibility study is to interpret the various technical approaches which could be followed to implement the project successfully with minimal risks.
In the world of software development, there are at least five risk management methodologies. Boehm’s Software Risk Management model focuses on the concept of “risk exposure” as defined by the relationship where the probability of an unsatisfactory outcome and the loss due to the unsatisfactory outcome determine the valence of the risk event. The method developed by Boehm is the original Risk Management
In [20] Buyukozkan & Ruan used the Choquet integral aggregation approach to assess the important effects and interactions among the risks of software development. They retrieved the risk factors of software development by studying an extensive range of literature, and they examined an array of risks types including development environment risks, product engineering risks, and program constraint-associated risks like the main dimensions of risks. Factors linked to product risks of engineering entail design, requirements, unit and code tests, testing and incorporation, and specialists in engineering. The development environment risks factors entail development system, development process, management methods, management process, and the environment of work. Contact, resource, and program consolidate are the kind of factors that affect the risks of program