Ans: A direct measure is obtained by applying measurement rules directly to the phenomenon of interest. Information systems analysis and design is a method used by companies ranging from IBM to PepsiCo to Sony to create and maintain information systems that perform basic business functions such as keeping track of customer names and addresses, processing orders, and paying employees.
The main goal of systems analysis and design is to improve organizational systems, typically through applying software that can help employees accomplish key business tasks more easily and efficiently. As a systems analyst, you will be at the center of developing this software. Ans: concurrency of components, lack of a global clock and independent failures of components and the ability to work well when the load or the number of users increases — failure handling, concurrency of components, transparency and providing quality of service view more..
Ans: the wide range of applications in use today, from relatively localized systems as found, for example, in a car or aircraft to globalscale systems involving millions of nodes, from data-centric services to processorintensive tasks, from systems built from very small and relatively primitive sensors to those incorporating powerful computational elements, from embedded systems to ones that support a sophisticated interactive user experience, and so on.
Ans: The task of a web search engine is to index the entire contents of the World Wide Web, encompassing a wide range of information styles including web pages, multimedia sources and scanned books view more.. Ans: The growth of the World Wide Web as a repository of information and knowledge; the development of web search engines such as Google and Yahoo to search this vast repository view more.. Ans: The engineering of MMOGs represents a major challenge for distributed systems technologies, particularly because of the need for fast response times to preserve the user experience of the game.
Ans: a very different style of underlying architecture from the styles mentioned above for example client-server , and such systems typically employ what is known as distributed event-based systems. Ans: the emergence of ubiquitous computing coupled with the desire to support user mobility in distributed systems view more..
Ans: The Internet is also a very large distributed system. It enables users, wherever they are, to make use of services such as the World Wide Web, email and file transfer. Indeed, the Web is sometimes incorrectly equated with the Internet. Q 2 in the above equation considers only functional requirements and ignores non-functional requirements. In order to consider non-functional requirements, it is necessary to consider the degree to which requirements have been validated.
This can be represented by the following equation. The success of a software project depends largely on the quality and effectiveness of the software design. Hence, it is important to develop software metrics from which meaningful indicators can be derived. With the help of these indicators, necessary steps are taken to design the software according to the user requirements. Various design metrics such as architectural design metrics, component-level design metrics, user-interface design metrics, and metrics for object-oriented design are used to indicate the complexity, quality, and so on of the software design.
These metrics focus on the features of the program architecture with stress on architectural structure and effectiveness of components or modules within the architecture. In architectural design metrics, three software design complexity measures are defined, namely, structural complexity, data complexity, and system complexity. System complexity is the sum of structural complexity and data complexity and is calculated by the following equation.
The complexity of a system increases with increase in structural complexity, data complexity, and system complexity, which in turn increases the integration and testing effort in the later stages. In addition, various other metrics like simple morphology metrics are also used.
These metrics allow comparison of different program architecture using a set of straightforward dimensions. A metric can be developed by referring to call and return architecture. This metric can be defined by the following equation. For example, there are 11 nodes and 10 arcs. Here, Size can be calculated by the following equation.
Depth is defined as the longest path from the top node root to the leaf node and width is defined as the maximum number of nodes at any one level.
Coupling of the architecture is indicated by arc-to-node ratio. This ratio also measures the connectivity density of the architecture and is calculated by the following equation. Quality of software design also plays an important role in determining the overall quality of the software. Many software quality indicators that are based on measurable design characteristics of a computer program have been proposed.
To calculate DSQI, a number of steps are followed, which are listed below. To calculate DSQI, the following values must be determined. Once all the values from S 1 to S 7 are known, some intermediate values are calculated, which are listed below. Once all the intermediate values are calculated, OSQI is calculated by the following equation. In conventional software, the focus of component — level design metrics is on the internal characteristics of the software components; The software engineer can judge the quality of the component-level design by measuring module cohesion, coupling and complexity; Component-level design metrics are applied after procedural design is final.
Various metrics developed for component-level design are listed below. By using the above mentioned measures, module-coupling indicator m c is calculated by using the following equation. Note that K, a, b, and c are empirically derived. The values of m c and overall module coupling are inversely proportional to each other.
In other words, as the value of m c increases, the overall module coupling decreases. Complexity Metrics: Different types of software metrics can be calculated to ascertain the complexity of program control flow. One of the most widely used complexity metrics for ascertaining the complexity of the program is cyclomatic complexity.
Many metrics have been proposed for user interface design. However, layout appropriateness metric and cohesion metric for user interface design are the commonly used metrics. Layout Appropriateness LA metric is an important metric for user interface design. These layout entities help the users in completing their tasks easily. In to complete a given task with the help of GUI, the user moves from one layout entity to another.
Appropriateness of the interface can be shown by absolute and relative positions of each layout entities, frequency with which layout entity is used, and the cost of changeover from one layout entity to another. Cohesion metric for user interface measures the connection among the onscreen contents. Cohesion for user interface becomes high when content presented on the screen is from a single major data object defined in the analysis model. On the other hand, if content presented on the screen is from different data objects, then cohesion for user interface is low.
In addition to these metrics, the direct measure of user interface interaction focuses on activities like measurement of time required in completing specific activity, time required in recovering from an error condition, counts of specific operation, text density, and text size.
Once all these measures are collected, they are organized to form meaningful user interface metrics, which can help in improving the quality of the user interface. In order to develop metrics for object-oriented OO design, nine distinct and measurable characteristics of OO design are considered, which are listed below. Halstead proposed the first analytic laws for computer science by using a set of primitive measures, which can be derived once the design phase is complete and code is generated.
These measures are listed below. This paper presents, in the context of case-based reasoning, two practical classification rules that allow appropriate emphasis on each type of misclassification as per the project requirements. In recent decades, software has become ubiquitous. Almost all modern engineered systems include significant software subsystems; this includes systems in the transportation, finance, education, healthcare, legal, military, and business sectors. Along with the increase in software utility, capability, cost, and size there has been a corresponding growth in methods, models, tools, metrics and standards, which support software engineering.
Chapter 10 of the SWEBOK discusses modeling principles and types, and the methods and tools that are used to develop, analyze, implement, and verify the models. Table 1 identifies software engineering features for different life-cycle phases. Goodreads helps you keep track of books you want to read. Want to Read saving…. Want to Read Currently Reading Read.
Software quality View larger. Donate to arXiv Metrics and Models in Software Quality Engineering, Second Edition , is the definitive book on this essential topic of software development.
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