Computer Science theory fails to cover large areas of computer usage. Existing theory often has assumptions which turn out not to be realistic in current practice. One problem is the lack of realistic, well-founded, data in most areas of computer usage and software development.
Theories deal with computation more then they do with practical engineering part of computer science, computer engineering, information technology etc. They are very useful when you want to write simulation programs and do research or analyse something statistically and you need efficient algorithms etc. However, in practical terms it is not of use, as you have said.
What could be done is to encourage researchers to explore the more immediate problems that developers and professionals are having, to listen to what troubles them in development processes and possibly create or find better solutions when it comes to development efficiency, reducing redundancy, developing better standardized tools, protocols etc. It theory were to deal with these fields that are actually the source of all headaches we (developers) are having, then in truth, theories of computer science and IT will have been made useful.
A theory is first based on assumption, then it is tested with hypothesis, then it is implemented in a environment. Similar is the case with the computer science theory. They set a benchmark for each theory that cannot be achieved in current practice. The market practice the theory which gives profit, is reliable and easy to use. Also there is un realistic data available for most of the theories on which further theories are made. that makes a sum of unrealistic approaches. One person if follows the realistic approach, then no one gives credit to the originality, rather than focus on following the old theories and making the next theory on it.
what makes to think so? in "Computer Science theory fails to cover large areas of computer usage", please define "computer science theory", in order for others (or at least me) to respond.
Theory tries to provide an explanation for "why" particular phenomena behave as they do. Theory uses some not always stated assumptions and accepted reasoning techniques such as logic, set theory, or other areas of mathematics to build an explanation. Good theory is evidence based and provides opportunities to make useful predictions in real-world, practical areas.
Here you are :) I think you already have partial answer, albeit you also need to change your query a bit. Earlier you said that ".. Existing theory -often- has assumptions.." and now you mentioned that ".. Theory uses some -not always- stated assumptions ..". I think it is reasonable to assume that 'not always' is similar to 'sometimes'. If so, then you have contradiction as 'sometimes' and 'often' are opposite. So, I think "theory does not fail OFTEN otherwise it ceases to be a theory. In practice, we need to adapt the solution a bit to get the desired results. Again, I am not sure if I understood the contest when you said "computer usage", but for software development, theories are of great help.
Sanjay, I think you misunderstood. The not always refers to the assumptions being stated. There are always assumptions.
I want to express my humble opinion on this very important question. I absolutely agree with both Magel Kenneth and Muhammad Usman Tariq about any assumptions for a theory. These assumptions play crucial role during all future events. In my view, the assumptions are the environmental conditions (demands, constraints, etc). Using these assumptions, we first build a mathematical model, then we create a methodology and a solution approach (notions and definitions,
theorems and lemmas, etc), then we develop data structures, algorithms, etc. Now a question arrives: How these assumptions are relevant to reality? This is very important question. In my view, the researcher's theories don't count any reality, and therefore there exists a large Research-Practice gap. The researchers create their theories within own cabinet with the non-real life.assumptions about the market. I want to ask: Can the market be adapted to the Researcher's theories? I don't think that it was possible in reality. Thus, it turns out that the researchers create their theories for themselves only. To express my thought more clearly, I want to mention about one literary personage from my favourite Anton Chekhov's story called "Ionich" on the link http://www.eldritchpress.org/ac/jr/192.htm . I mean "Vera Iosifovna" that writes the novels "of what never happens in real life". Sometimes it seems to me that: most of science papers are more like to stories "of what never happens in real life"; most of science books are more like to novels "of what never happens in real life".
IMHO the premise of the question is false: there are at least (sic!) two well-established areas of Computer Science (in the broadest possible sense) mainly devoted to the relevance and usefulness of theories, methods, techniques, tools and applications of Computer Science (in a more narrow sense, e.g. mathematical or physical aspects):
(1) Human-Computer-Interaction, aka Usability Research, or Software Ergonomics in Europe): as old as 1962, grown tremendously since ca 1985, with all you might want: encyclopedia, handbooks, textbooks, conferences, institutes, companies, curricula, associations, online bilbiography since 1998, international standards, patents, etc. etc. I know many institutes and people working in this area since ages ...
(2) Experimental Software Engineering, also started up very early in the life of CS, e.g. Barry Boehm, with a wealth of information about what works and what doesn't work in Computer Science and its applications, trying to filter out myths and hypes from facts and laws (see Handbook of Software and Systems Engineering: Empirical Observations, Laws and Theories). I know at least two institutes, one in Germany one in USA, which are exclusively doing research and development in this area since more than 10 years ...
The problem is, apparently, that the existence of both disicplinary fields (and potentially other ones I am not aware of ;-) and the dissemination of their accomplishments is not optimally communicated to those who need their results and insights. What can we do about it !?
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