Download Crisis Management for Software Development and Knowledge by Sergey V. Zykov PDF

By Sergey V. Zykov

This good dependent publication discusses lifecycle optimization of software program initiatives for problem administration by way of software program engineering tools and instruments. Its results are in response to classes realized from the software program engineering hindrance which begun within the Nineteen Sixties. The booklet provides a scientific method of conquer the difficulty in software program engineering relies which not just relies on technology-related but in addition on human-related components. It proposes an adaptive technique for software program product improvement, which optimizes the software program product lifecycle as a way to keep away from “local” crises of software program construction. the overall lifecycle trend and its phases are mentioned, and their impression at the time and price range of the software program product improvement is analyzed. The publication identifies key benefits and downsides for numerous versions chosen and concludes that there's no “silver bullet”, or common version, which fits all software program items both good. It methods software program structure when it comes to procedure, facts and method views and proposes an incremental method for crisis-agile improvement of large-scale, allotted heterogeneous purposes. The ebook introduces a couple of really expert techniques that are favourite in yet are frequently neglected typically writings as a result of their vendor-specificity. In doing so, the e-book builds a beneficial bridge from educational conceptions of software program engineering to the area of software program engineering perform. With its systematic assurance of alternative software program engineering methodologies and the provided wealthy platforms engineering examples the e-book should be precious for a broader audience.

Show description

Read Online or Download Crisis Management for Software Development and Knowledge Transfer PDF

Similar intelligence & semantics books

The Artificial Life Route To Artificial Intelligence: Building Embodied, Situated Agents

This quantity is the direct results of a convention during which a few top researchers from the fields of synthetic intelligence and biology amassed to envision no matter if there has been any flooring to imagine new AI paradigm used to be forming itself and what the basic parts of this new paradigm have been.

An Introduction to Computational Learning Theory

Emphasizing problems with computational potency, Michael Kearns and Umesh Vazirani introduce a couple of relevant subject matters in computational studying idea for researchers and scholars in synthetic intelligence, neural networks, theoretical machine technology, and statistics. Computational studying thought is a brand new and quickly increasing region of analysis that examines formal types of induction with the pursuits of studying the typical tools underlying effective studying algorithms and opting for the computational impediments to studying.

Ontology-Based Multi-Agent Systems

The Semantic net has given loads of impetus to the improvement of ontologies and multi-agent platforms. a number of books have seemed which debate the advance of ontologies or of multi-agent structures individually on their lonesome. The transforming into interplay among agnets and ontologies has highlighted the necessity for built-in improvement of those.

Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

The tough and fuzzy set ways offered right here open up many new frontiers for endured learn and improvement. Computational Intelligence and have choice presents readers with the heritage and primary principles at the back of function choice (FS), with an emphasis on innovations according to tough and fuzzy units.

Extra info for Crisis Management for Software Development and Knowledge Transfer

Example text

E. to estimate possible benefits for the customer and the developer depending on their investments. For certain lifecycle stages, such as testing and maintenance, we can use specific metrics. Every lifecycle stage has its own metrics. The testing stage, for instance, can use such metrics as complexity of a separate module, number of lines (typically measured in KLOC), number of different operators in a module, relative number of errors detected for each KLOC and so on. It is required to analyze the total number of failures and identify their lifecycle phases in order to manage detection and removal of the defects injected prior to testing.

For example, in case of an online store, a problem could be the internet throughput because the actual number of users is significantly more than the planned one. The new technological constraints require database server change for a more data intensive one; the new software product should support transactions, and the overall performance of the system in terms of response time should remain at least at the same level as before. Adaptive maintenance is related to the migration of an existing software product into a new environment.

What does the choice of the software product lifecycle depend on? Primarily, it depends on the nature and size of the product. In this respect, analysis and specification of requirements and constraints for the basic product scope define the selection. The key constraints are the product size, development time and project risks. For instance, spiral model is strongly dependent on risk assessment, so it makes sense to apply it in case risk analysis is required. Lifecycle model choice influences the economics of the project, including return on investment.

Download PDF sample

Rated 4.85 of 5 – based on 46 votes