Department of Computer Science

Permanent URI for this communityhttps://repository.cuilahore.edu.pk/handle/123456789/16

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Author: search.filters.author.Dr. Ghulam RasoolSubject: search.filters.subject.fa17

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    Software Measurements at Small and Medium Enterprises
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2017) Muhammad Noman; FA14-MSCS-018; LHR TP 6871; Dr. Ghulam Rasool
    Software measurement processes are crucial to recognize, assess, identify and measure software products and resources. However, the successful measurement processes implementation is a challenging task in small and medium enterprises (SMEs). The main goal of this thesis is to propose a measurement framework to assess the significant factors that may influence the successful measurement processes implementation in Software SMEs. A multi-method research technique is used to perform this research. A systematic mapping study is conducted to extract the significant factors, challenges, and limitations that may affect the successful implementation of measurement processes in software organizations. A search string is prepared and, applied to different databases (IEEE, ACM, Springer etc) to identify the relevant studies. In total, 24 primary studies are finalized after applying inclusion and exclusion criteria. All the primary studies are explored comprehensively and, identified success factors are categorized in seven major constructs. A measurement framework is proposed for adaptation of measurement processes in software SMEs based on the findings of the mapping study. A total of seven constructs (success factors) are defined in the proposed framework. The proposed framework is evaluated using an online survey. An online survey is conducted from the software professionals in software organizations of Pakistan. In total, 217 responses were collected and a data set is prepared. Structural equation modeling (SEM) technique is used to evaluate the data set. Statistical tools (AMOS and SPSS) are used for factor analysis and hypothesis testing. The statistical results shows that the proposed framework is acceptable due to satisfactory values of model fit indices and use of reliable items in the path diagram. In hypotheses testing, two of the seven constructs (External Forces, Management Commitment) are found to have a significant effect on successful measurement processes in software organizations. The proposed framework can be extended by adding more factors and it can also be verified in software industries of different countries.
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    Recovery of Anti-Patterns from Microservices
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) Sabahat Atta; FA17-RCS-028; LHR TP 5980; Dr. Ghulam Rasool
    Microservices have brought an evolution in the Service Oriented Architecture by introducing high independence at various levels. These services provide independent development, service to service communication, individual database per service, independent deployment, and maintenance, etc. The service-oriented systems support the quick implementation of customized changes to software applications. These frequent changes might result in introducing some feeble solutions. These solutions commonly known as “Anti-Patterns”, can negatively impact the quality of the microservices. Another reason for anti-patterns occurrence may be due to the migration of software applications developed on monolithic architecture to microservices architecture. This process demands a high knowledge of microservices-based design patterns and best practices to avoid flaws that might instigate while migration from centralized to a distributed environment. In this research, we have selected 18 microservices related anti-patterns and proposed an approach for their detection. We found only a single approach that presented an algorithm to detect microservices specific Anti-Patterns [1]; the study focused on detecting five anti-patterns. However, our proposed approach differs from the state-of-the-art approach, as, firstly, we focused on the detection of a large number of anti-patterns. Secondly, we have implemented reverse engineering on microservices-based systems and then detected anti-patterns from these systems. Our research focuses on the detection of microservices specific anti-patterns from microservices-based software applications. Our approach is developed as an automated approach supplemented with an add-in for Sparx System EA for the automatic detection of anti-patterns from microservices-based systems. We have evaluated our approach using precision and recall metrics