Containerization

Although having its origins in the late 1780s or earlier, the global standardisation of containers and container handling equipment was one of the important innovations in 20th century logistics.

By the 1830s, railroads on several continents were carrying containers that could be transferred to trucks or ships, but these containers were invariably small by today's standards. Originally used for shipping coal on and off barges, 'loose boxes' were used to containerize coal from the late 1780s, on places like the Bridgewater Canal. By the 1840's, iron boxes were in use as well as wooden ones. The early 1900s saw the adoption of closed container boxes designed for movement between road and rail.

Cost overrun

Cost overrun is defined as excess of actual cost over budget. Cost overrun is also sometimes called "cost escalation," "cost increase," or "budget overrun." However, cost escalation and increases do not necessarily result in cost overruns if cost escalation is included in the budget.

Cost overrun is common in infrastructure, building, and technology projects. One of the most comprehensive studies of cost overrun that exists found that 9 out of 10 projects had overrun, overruns of 50 to 100 percent were common, overrun was found in each of 20 nations and five continents covered by the study, and overrun had been constant for the 70 years for which data were available. For IT projects, an industry study by the Standish Group (2004) found that average cost overrun was 43 percent, 71 percent of projects were over budget, over time, and under scope, and total waste was estimated at US$55 billion per year in the US alone.

Rapid application development

Rapid application development (RAD), is a software development process developed initially by James Martin in 1991. The methodology involves iterative development, and the construction of prototypes. Traditionally the rapid application development approach involves compromises in usability, features, and/or execution speed. It is described as a process through which the development cycle of an application is expedited. Rapid Application Development thus enables quality products to be developed faster, saving valuable resources

H2 (DBMS)

A subset of the SQL (Structured Query Language) standard is supported. The main programming APIs are SQL and JDBC, however the database also supports using the PostgreSQL ODBC driver by acting like a PostgreSQL server.

It is possible to create both in-memory tables, as well as disk-based tables. Tables can be persistent or temporary. Index types are hash table and tree for in-memory tables, and b-tree for disk-based tables. All data manipulation operations are transactional. Table level locking and multiversion concurrency control are implemented. The 2-phase commit protocol is supported as well, but no standard API for distributed transactions is implemented.

Database normalization

Database normalization, sometimes referred to as canonical synthesis, is a technique for designing relational database tables to minimize duplication of information and, in so doing, to safeguard the database against certain types of logical or structural problems, namely data anomalies. For example, when multiple instances of a given piece of information occur in a table, the possibility exists that these instances will not be kept consistent when the data within the table is updated, leading to a loss of data integrity. A table that is sufficiently normalized is less vulnerable to problems of this kind, because its structure reflects the basic assumptions for when multiple instances of the same information should be represented by a single instance only.