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Telecommunication has a decisive role in the development of technology in the current era. The number of mobile users with multiple SIM cards is increasing every second. Hence, telecommunication is a significant area in which big data technologies are needed. Competition among the telecommunication companies is high due to customer churn. Customer retention in telecom companies is one of the major problems. The paper aims to discuss this issue.

The authors recommend an Intersection-Randomized Algorithm (IRA) using MapReduce functions to avoid data duplication in the mobile user call data of telecommunication service providers. The authors use the agent-based model (ABM) to predict the complex mobile user behaviour to prevent customer churn with a particular telecommunication service provider.

The agent-based model increases the prediction accuracy due to the dynamic nature of agents. ABM suggests rules based on mobile user variable features using multiple agents.

The authors have not considered the microscopic behaviour of the customer churn based on complex user behaviour.

This paper shows the effectiveness of the IRA along with the agent-based model to predict the mobile user churn behaviour. The advantage of this proposed model is as follows: the user churn prediction system is straightforward, cost-effective, flexible and distributed with good business profit.

This paper shows the customer churn prediction of complex human behaviour in an effective and flexible manner in a distributed environment using Intersection-Randomized MapReduce Algorithm using agent-based model.

The purpose of this paper is to describe an approach towards code validation of RISC microcontrollers, which helps to automate software debugging. A static machine code analysis which checks the appropriateness of instructions in a sequence to identify any logical mistakes and also to identify redundant codes appearing in a program for the target processor is presented.

Validation is done with the help of rules of inferences formulated for the target processor. The rules govern the occurrence of illegitimate/out of place instructions and code sequences for executing the computational and integrated peripheral functions. The stipulated rules are encoded in propositional logic formulae and their compliance is tested in all possible execution paths of the application programs. An incorrect sequence of machine code pattern is identified using slicing techniques on the control flow graph generated from machine code.

The results explain that the technique is independent of compiler/assembler and contributes to early detection of software bugs that are otherwise hard to detect. Program states are identified mainly with machine code pattern, which drastically reduces the state space creation contributing to an improved state‐of‐the‐art model checking.

Though the technique described is general, the implementation is highly architecture oriented, and hence the feasibility study is conducted only on PIC16F87X microcontrollers.

This validation tool can be integrated to the system development environment resulting in improved software quality and reduced debugging time.

It is a novel and original approach at machine code level applicable to a wide range of processors once appropriate rules are available.