Software intelligence

Software Intelligence is insight into the structural condition of software assets produced by software designed to analyze database structure, software framework and source code to better understand and control complex software systems in Information Technology environments. Similarly to Business Intelligence (BI), Software Intelligence is produced by a set of software tools and techniques for the mining of data and software inner-structure. End results are information used by business and software stakeholders to make informed decisions, measure the efficiency of software development organizations, communicate about software health, prevent software catastrophes.
History.
Software Intelligence has been used by Kirk Paul Lafler, an American engineer, entrepreneur, and consultant, and founder of Software Intelligence Corporation in 1979. At that time, it was mainly related to SAS activities, in which he has been an expert since 1979.
In the early 1980s, Victor R. Basili participated in different papers detailing a methodology for collecting valid software engineering data relating to software engineering, evaluation of software development, and variations.
In 2004, different software vendors in software analysis start using the terms as part of their product naming and marketing strategy. Then in 2010, Ahmed E. Hassan and Tao Xie defined Software Intelligence as a ""practice offering software practitioners up-to-date and pertinent information to support their daily decision-making processes and Software Intelligence should support decision-making processes throughout the lifetime of a software system". They go on by defining Software Intelligence as a "strong impact on modern software practice"" for the upcoming decades.
Capabilities.
Because of the complexity and wide range of components and subjects implied in software, Software intelligence is derived from different aspects of software:
Components.
The capabilities of Software intelligence platforms include an increasing number of components:
User Aspect.
Some considerations must be made in order to successfully integrate the usage of Software Intelligence systems in a company. Ultimately the Software Intelligence system must be accepted and utilized by the users in order for it to add value to the organization. If the system does not add value to the users' mission, they simply don't use it as stated by M. Storey in 2003.
At the code level and system representation, Software Intelligence systems must provide a different level of abstractions: an abstract view for designing, explaining and documenting and a detailed view for understanding and analyzing the software system.
At the governance level, the user acceptance for Software Intelligence covers different areas related to the inner functioning of the system as well as the output of the system. It encompasses these requirements: 
Applications.
Software intelligence has many applications in all businesses relating to the software environment, whether it is software for professionals, individuals, or embedded software.
Depending on the association and the usage of the components, applications will relate to:
Marketplace.
The Software Intelligence is a high-level discipline and has been gradually growing covering applications listed above. There are several markets driving the need for it: 