Why High Degree of Coupling Among Components of a Software make Maintenance Difficult

  • Explain why a high degree of coupling among components of a software system can make maintenance of the system difficult. Provide at least one example that supports your answer.
  • Elaborate on two maintenance strategies that you would apply to lessen the effect of an already tightly coupled software that you have to maintain for an organization that requires 100% uptime on its safety-critical system. Provide a justification as to why you would implement these strategies over other options that are available. Describe how your strategies would change if the system only required 90% uptime and could be shut down for short periods of time during nonbusiness hours.
  • identify at least two methods by which we can determine if a legacy system should remain as legacy or it should be upgraded into a new software system. Explain these two methods and how they are applied.
  •  describe at least two ways software engineers can measure the impact of a proposed change to a software system.

Why A High Degree Of Coupling Among Components Of A Software System Can Make Maintenance Of The System Difficult

High coupling refers to a situation where changes made to one component have a ripple impact on other components, resulting in a complicated network of mutual dependency. It hinders the comprehension of the complete consequences of the change and intensifies the possibility of unintentionally causing adverse outcomes (Fregnan et al., 2019). Tight connection affects the ability to separate and test different parts unilaterally. As a result, the debugging process is increased as it becomes more challenging to ascertain whether an issue is isolated to a particular component or arises due to relationships with other components. Systems with a high degree of interconnectivity are typically less adaptable and expandable since modifying one component of the system can help during adjustments in many parts (Fregnan et al., 2019). Consequentially, it results in an elevated level of strain needed to modify the system in response to evolving demands or to expand its capacity to accommodate higher workloads. When the components are closely interconnected, it becomes more difficult to maintain the codebase. Developers must possess comprehensive knowledge of the entire system in order fully understand the impacts of their modifications (Zhong et al., 2023). In the long-run, the progress of development is hindered and amplifying the probability of introducing errors.

For example, the case of a web application that has interconnected front-end and back-end components. If the front-end is highly dependent on particular data structures or APIs offered by the back-end, any modifications made to those structures or APIs can necessitate matching adjustments to the front-end code. This not only doubles the burden on developers but also poses the danger of introducing defects or disparities if the modifications are not adequately synchronized. On the other hand, if the front-end and back-end components were not tightly connected and had clearly defined interfaces and minimum interdependencies, modifications to one component could be implemented more freely, thereby decreasing the likelihood of unanticipated impacts and simplifying maintenance tasks (Zhong et al., 2023).

Strategies for Maintaining Tightly Coupled Software to Lessen the Effect of an Already Tightly Coupled Software

In order to mitigate the influence of a program that is already tightly integrated for a safety-critical system that demands uninterrupted operation, the following maintenance procedures might be implemented:

Incremental Refactoring:

            Incremental refactoring is the process of deconstructing tightly connected software into smaller, easier to manage parts while maintaining its exterior behavior (Li et al., 2023). Through a steady process of refactoring, the potential for causing disruptions to vital activities is minimized, while also reducing the overall complexity of the system. The approach enables ongoing enhancement while ensuring the necessary operational availability.

Redundancy and Failover Mechanisms:

Developing redundancy and failover solutions involves setting up backup systems and procedures to guarantee continuous functioning in the case of a failure. The technique can incorporate redundant equipment, copying of data, and failover protocols to easily transition to backup components in the event of primary component failure. Redundancy aids in reducing the consequences of tightly interconnected components malfunctioning, thereby enhancing the overall dependability and continuous operation of the system (Li et al., 2023).

Changes for 90% Uptime Requirement with Nonbusiness Hours Downtime:

Scheduled Maintenance Windows:

 Periodic maintenance windows can be designed to meet the requirements of 90% uptime and allow for system shutdowns during nonbusiness hours. The importance of this technique is that it enables for scheduled periods of inactivity at less busy times, such as late at night or on weekends, to carry out essential maintenance tasks without interrupting crucial operations during busy periods.

Flexible Redundancy and Failover:

By reducing the required uptime, there is increased freedom to incorporate redundancy and failover systems, which results in slightly extended failover durations or a less fast response to failures. By implementing this approach, it is possible to reduce maintenance expenses and system difficulty without compromising the system’s stability.

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Methods By Which We Can Determine If A Legacy System Should Remain As Legacy Or It Should Be Upgraded Into A New Software System

The first technique for determining whether a legacy system should remain as-is or updated to a new software system is through technical assessment. A technical assessment is the process of reviewing the existing status of a legacy system from a technical perspective to determine if it is suitable for future usage and if it aligns with the developing demands of the organization (Irani et al., 2023). Such assessment requires assessing various elements, including the framework’s scalability, efficiency, safety, maintainability, and interoperability with modern technology and integration capabilities. Additionally, it entails taking into account the amount of technical debt accumulated in the outdated system, and presence of proficient resources for the upkeep and improvement of the system. Organizations can obtain useful knowledge into the technical constraints of a system and its ability to meet future requirements by conducting a technical assessment (Irani et al., 2023). The information obtained aids in assessing the need for an upgrade to rectify technological shortcomings and align with the organization’s long-term objectives.

Cost-benefit analysis is the second approach used to decide if a legacy system should be kept as it is or upgraded to a new software system. A cost-benefit analysis is conducted to assess the expenses and advantages of keeping the current legacy system versus upgrading to a new software system (Irani et al., 2023). Expenses comprise continuous upkeep, assistance, and any hazards linked to security weaknesses and malfunctions of the system. Benefits can include increased productivity, greater protection, and the possibility of expanding the business. The approach entails calculation of the whole cost of owning and operating the existing system, which incorporates expenses related to maintenance, support, and potential dangers.

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Ways Software Engineers Can Measure The Impact Of A Proposed Change To A Software System

Software engineers can assess the effects of a recommended modification to a software system through different methods, such as code analysis and testing. Applying code analysis and testing both before and after implementing the suggested change can assist in quantifying its impact (Agrawal & Singh, 2020). Engineers can employ several tools, such as integration tests, static code analyzers, regression tests and unit tests to gauge the impact of the changes on the entire codebase and system functionality. Quantitative statistics on the impact of the modification can be obtained using metrics such as code coverage, performance benchmarks, and test pass rates.

Software engineers can also determine assess the impact of a suggested change to a software system through the use of monitoring and analytics. Integrating monitoring and analytics tools into the software system enables real-time tracking of the effects of a proposed adjustment (Agrawal & Singh, 2020). Moreover, engineers can apply logging, analytics, and tracing techniques to collect data on system behavior, error rates, reaction times, and other pertinent performance characteristics. Data of that type can offer valuable insights into the impact of the change on the system’s reliability, speed, and user experience.

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