Fuzzy Logic Concepts Usage in Software Engineering

Utilizing the estimation models in the field of software engineering, the prediction of significant attributes in future entities can be achieved, for example, productivity, software development effort, software development cost, and software reliability.

The management of software-related projects must be carried out accurately and the prediction and scheduling of effort estimation must be done based on the time to maintain the software system effectively. This process is considered as crucial in software systems.

There are so many techniques for estimation prediction, among which analogy- related estimation is a commonly utilized approach by researchers as well as industry, especially in software effort estimation. In case of analogy-related software effort estimation there are limitations. The categorical data (nominal or ordinal scale) is usually used for describing software projects, such as, very high, high, low, and very low. The attributes that are referred in this fuzzy logic are referred to as linguistic values. The challenge is faced by the concept of measurement in the software business, because of two major key motives: lack of standards, and most of the time the nature of software attributes is qualitative instead of quantitative.

Thus, at present there is a lack of a standardized estimation model to estimate software cost, effort, productivity, etc. It is still a challenge in the field of software work. Even though research is continuously carried out the estimation model is compromised with precision and certainty of value.

Soft computing might be the best solution for such problems since it has the features like the ability to work with uncertainty, learning from experience, and is tolerant of imprecise information that are likewise the key issues of software estimations.

Fuzzy set theory principle was first discussed by Zadeh. An approach that is well-suited for linguistic values was found to be the fuzzy set model principle. The creation of a quantitative framework is the main objective for fuzzy set theory. An unclear gathering of information can be limited by means of this model. The information acquired will be usually described in the form of natural language.

We can join the benefits of fuzzy logic with key challenges of software effort estimation. In recent studies it is found that for describing the categorical data the fuzzy set is found to be effective when compared to other classical intervals (Idri et al. 2000, 2001).

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