EMPLOYEE PRESENCE APPLICATION USING SWAFOTO AND LOCATION BASED SERVICE AT THE FACULTY OF SCIENCE AND TECHNOLOGY AT UNIVERSITAS TERBUKA

The Covid-19 pandemic gave birth to a policy of limiting employees who work from office (WFO) and employees who work from home (WFH). At the Faculty of Science and Technology (FST) of the Universitas Terbuka, attendance for employees who do WFH uses Microsoft Form. This is considered impractical and raises several problems. This study will develop a presence application by utilizing selfies and location-based services based on Android. The purpose of this study is to assist in processing attendance data by knowing the location of the employee and authentication using the employee's face. The system can process data into reports that can help faculty know the activities and performance of employees. The software development methodology uses Agile Development. This model has stages including planning, design, develop, test, release, and planning stages. Each stage in the Agile Development model is carried out in an organized and structured manner according to agreed rules and solutions. Software testing uses Black Box Testing which will test the functions, inputs, and outputs of software or applications based on needs. There are 20 test scenarios performed for users and administrators. From testing using Black Box Testing, 100% of the functions run well, so it can be concluded that the application is suitable for use in the Faculty of Science and Technology of the Universitas Terbuka

Impact of Software Uncertainty on Reliability of Agile (Object-Oriented Software) Product Development Model

The aim of this paper is to describe software system product uncertainty analysis with the assistance of Unc_Sidekick for Uncertainty and Sensitivity Analysis. This tool is predicated on Monte Carlo (MC) analysis that's supported play acting multiple model evaluations with probabilistically agile software system comes input. The results of those evaluations are wont to confirm in software each the uncertainty system predictions and therefore the input variables that drive this uncertainty. This technique is important in things wherever a call needs to be taken supported the agile software system product results; typical examples embody risk and failure management systems, monetary analysis and plenty of others. It’s additionally extremely suggested as a part of agile software system validation, even wherever the software’s are used for analytic functions, as part of software system product building. Unc_Sidekick permits a hunt of the area of attainable various model assumptions and structure on the prediction of the product, thereby testing each the standard of the agile software system product and therefore the hardiness of the product and model primarily based abstract thought

Using Variability Management in Mobile Application Test Modeling

Mobile applications are developed to run on fast-evolving platforms, such as Android or iOS. Respective mobile devices are heterogeneous concerning hardware (e.g., sensors, displays, communication interfaces) and software, especially operating system functions. Software vendors cope with platform evolution and various hardware configurations by abstracting from these variable assets. However, they cannot be sure about their assumptions on the inner conformance of all device parts and that the application runs reliably on each of them—in consequence, comprehensive testing is required. Thereby, in testing, variability becomes tedious due to the large number of test cases required to validate behavior on all possible device configurations. In this paper, we provide remedy to this problem by combining model-based testing with variability concepts from Software Product Line engineering. For this purpose, we use feature-based test modeling to generate test cases from variable operational models for individual application configurations and versions. Furthermore, we illustrate our concepts using the commercial mobile application “runtastic” as example application

Information Extraction for System-Software Safety Analysis: Calendar Year 2007 Year-End Report

This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis on the models to identify possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations; 4) perform discrete-time-based simulation on the models to investigate scenarios where these paths may play a role in failures and mishaps; and 5) identify resulting candidate scenarios for software integration testing. This paper describes new challenges in a NASA abort system case, and enhancements made to develop the integrated tool set

A Machine With Class: A Framework for Object Generation, Integration and Language Authentication (FROGILA)

The object technology model is constantly evolving to address the software crisis problem. This novel idea which informed and currently guides the design style of most modern scalable software systems has caused a strong belief that the object-oriented technology is the ultimate answer to the software crisis, i.e. applying an object-oriented development method will eventually lead to quality code. It is important to emphasise that object-orientedness does not make testing obsolete. As a matter of fact, some aspects of its very nature introduce new problems into the production of correct programs and their testing due to paradigmatic features like encapsulation, inheritance, polymorphism and dynamic binding as this research work shows. Most work in testing research has centred on procedure-oriented software with worthwhile methods of testing having been developed as a result. However, those cannot be applied directly to object-oriented software owing to the fact that the architectures of such systems differ on many key issues. In this thesis, we investigate and review the problems introduced by the features of the object technology model and then proceed to show why traditional structured software testing techniques are insufficient for testing object-oriented software by comparing the fundamental differences in their architecture. Also, by reviewing Weyuker’s test adequacy axioms we show that program-based testing and specification-based testing are orthogonal and complementary. Thus, a software testing methodology that is solely based on one of these approaches (i.e. program-based or specification-based testing) cannot adequately cover all the essential paths of the system under test or satisfactorily guarantee correctness in practice. We argue that a new method is required which integrates the benefits of the two approaches and further builds upon their individual strengths to create a more meaningful, practical and reliable solution. To this end, this thesis introduces and discusses a new automaton-based framework formalism for object-oriented classes called the Class-Machine and a test method that is based on this formalism. Here, the notion of a class or the idea behind classification in object-oriented languages is embodied within a machine framework. The Class-Machine model represents a polymorphic abstraction for heterogeneous families of Object-Machines that model a real life problem in a given domain; these Object-Machines are instances of different concrete machine types. The Class-Machine has an extensible machine implementation as well as an extensible machine interface. Thus, the Class-Machine is introduced as a formal framework for generating autonomous Object-Machines (i.e. Object-Machine Generator) that share common Generic Class-Machine States and Specific Object-Machine States. The states of these Object-Machines are manipulated by a set of processing functions (i.e. Class-Machine Methods and Object-Machine Methods) that must satisfy a set of preconditions before they are allowed to modify the state(s) of the Object-Machines. The Class-Machine model can also be viewed as a platform for integrating a society of communicating Object-Machines. To verify and completely test systems that adhere to the Class-Machine framework, a novel testing method is proposed i.e. the fault-finders (f²) - a distributed family of software checkers specifically designed to crawl through a Class-Machine implementation to look for a particular type of fault and tell us the location of the fault in the program (i.e. the class under test). Given this information, we can statistically show the distribution of faults in an object-oriented system and then provide a probabilistic assertion of the number and type of faults that remain undetected after testing is completed. To address the problems caused through the encapsulation mechanism, this thesis introduces and discusses another novel framework formalism that has complete visibility on all the encapsulated methods, memory states of the instance and class variables of a given Object-Machine or Class-Machine system under test. We call this the Class Machine Friend Function (CMƒƒ). In order to further illustrate all the fundamental theoretical ideas and paradigmatic features inherent within our proposed Class-Machine model, this thesis considers four different Class-Machine case studies. Finally, to further show that the Class-Machine theoretical purity does not mitigate against practical concerns, our novel object-oriented specification, verification, debugging and testing approaches proposed in this thesis are exemplified in an automated testing tool called: The Class-Machine Testing Tool (CMTT)

VOICE RECOGNITION SYSTEM: SPEECH-TO-TEXT

VOICE RECOGNITION SYSTEM:SPEECH-TO-TEXT is a software that lets the user control computer functions and dictates text by voice. The system consists of two  components , first component is  for processing acoustic signal which is captured by a microphone and second component is to interpret the processed signal, then  mapping of the signal to words. Model for each letter will be built using Hidden Markov Model(HMM). Feature extraction will be done using Mel Frequency Cepstral Coefficients(MFCC). Feature training of the dataset will be done using vector quantization and Feature testing of the dataset will be done using viterbi algorithm. Home automation will be completely based on voice recognition system

Diversity of graph models and graph generators in mutation testing

When custom modeling tools are used for designing complex safety-critical systems (e.g., critical cyber-physical systems), the tools themselves need to be validated by systematic testing to prevent tool-specific bugs reaching the system. Testing of such modeling tools relies upon an automatically generated set of models as a test suite. While many software testing practices recommend that this test suite should be diverse, model diversity has not been studied systematically for graph models. In the paper, we propose different diversity metrics for models by generalizing and exploiting neighborhood and predicate shapes as abstraction. We evaluate such shape-based diversity metrics using various distance functions in the context of mutation testing of graph constraints and access policies for two separate industrial DSLs. Furthermore, we evaluate the quality (i.e., bug detection capability) of different (random and consistent) model generation techniques for mutation testing purposes

Sequence-Based Specification of Embedded Systems

Software has become integral to the control mechanism of modern devices. From transportation and medicine to entertainment and recreation, embedded systems integrate fundamentally with time and the physical world to impact our lives; therefore, product dependability and safety are of paramount importance. Model-based design has evolved as an effective way to prototype systems and to analyze system function through simulation. This process mitigates the problems and risks associated with embedding software into consumer and industrial products. However, the most difficult tasks remain: Getting the requirements right and reducing them to precise specifications for development, and providing compelling evidence that the product is fit for its intended use. Sequence-based specification of discrete systems, using well-chosen abstractions, has proven very effective in exposing deficiencies in requirements, and then producing precise specifications for good requirements. The process ensures completeness, consistency, and correctness by tracing each specification decision precisely to the requirements. Likewise, Markov chain based testing has proven effective in providing evidence that systems are fit for field use. Model-based designs integrate discrete and continuous behavior; models have both hybrid and switching properties. In this research, we extend sequence-based specification to explicitly include time, continuous functions, nondeterminism, and internal events for embedded real-time systems. The enumeration is transformed into an enumeration hybrid automaton that acts as the foundation for an executable model-based design and an algebraic hybrid I/O automaton with valuable theoretical properties. Enumeration is a step-wise problem solving technique that complements model-based design by converting ordinary requirements into precise specifications. The goal is a complete, consistent, and traceably correct design with a basis for automated testing