Computer science topic 1- System fundamentals

1.1 Planning and system installation

1.1.1 Identify the context in which a new system is planned

Data gathering:

 In planning stages there will be process of investigation and research into current systems involving the following methods with their respective pros and cons:

• Interview

  • Pros- Detailed information with key people, two way communication and face to face

  • Con- Time consuming

• Questionnaire

  • Pros- Data can reach large audiences quickly and can be used to create extensive analysis. Can be fast and effective

  • Cons- Has to be very well designed otherwise people may not answer properly or completely

• Document collection

  • Pros- Good quality and objective data about inner working of system such as inputs and outputs taking place within system

  • Cons- May be limited or inaccurate or outdated

• Observation

  • Pros- Can gain first hand and unbiased information

  • Cons- Observing may influence things or peoples behavior leading to unrealistic results

Requirements specification

Following collection of data, an analysis of the system needs to be done to fully grasp how it functions, with input process and outputs being identified alongside any problems (in current system).
This allows the analyst to understand what the requirements are for the new system, it is the guiding requirement specification list. This is a tightly controlled process for new system developments, so much so it appears in IEEE standard.

Requirement specification = Key document in a tradition life cycle that drives all subsequent work and serves as basis for project success and is often known as the success criteria

This stage of project takes into account context into which new system will be used and identifies any changes and new implementations required for new system.

Issues

Several issues are often involved with new system implementation. Clients may need retraining in order to learn to use new system and readjust, in extreme cases can lead to unemployment. Context of system in terms of contemporary technology also needs to be considered. Will the current hardware and software infrastructures be able to deal with new system´s technical requirements (e.g. bandwidth, storage processing)

1.1.2 Describe need for change management

Change management = Planned movement towards a future desired state

Change management can impact a variety or people or organisations depending on change required, hence requiring a structured approach

Can occur in many places like:

• Hardware

• Communication equipment and software

• System software

• All documentation and procedures associated with the running, support and maintenance of live systems

Why is it so important?
- Drastic changes that can impact everyone need to be managed and organised to ensure smooth transition to new system with minimal disruption

Real world example:

Change: Upgrading from Python 2 to Python 3

Potential Challenges:

Existing code might not work with Python 3.

Students and teachers may need to learn new syntax or libraries.

Benefits of Change Management:

A planned migration process can identify and fix compatibility issues before the upgrade.

Training sessions can help students and teachers adjust to the new version.

How does change management help address these challenges?

• Planning and communication- Clearly explanation of reason for changes, how it will be done and a timeline for the implementation of new system keeps everyone informed and reduces uncertainty

• Training and support- Providing helpful resources like tutorials helps users adapt minimizing frustration and ensures optimal use of new features.

• Risk management: In order to avoid complications throughout implementation, potential problems that might arise are identified throughout change and developing stages and mitigated.

Factors to consider for successful change management:

• People- How change impacts different user groups (teachers, students etc). Address concerns and provide appropriate support

• Technology- Ensure compatibility of existing infrastructure and data with new system through thorough testing

• Processes- How certain workflows might have to adapt to new system? Update documentation and procedures to reflect changes

1.1.3 Outline compatibility issues resulting from situations including legacy systems or business mergers.

Legacy systems and compatibility:

Legacy system- Older computer systems or software still in use that may not be compatible with newer tech, causing issues like:

• Data loss

• Erros

• Wasted time and resources

Business Mergers and compatibility

When businesses merge, existing computer systems need to be compatible in order to allow for transfer of data and smooth operating.

Example- Two different companies may use similar but different ID fields or variables to store the core values meaning that reformatting would be required to merge the data.

International interactions and compatibility

When organizations collaborate internationally, issues from differences in the follow may arise:

• Software- One company might use software incompatible with the other systems.

• Languages- Software interfaces and data might be in different languages, hindering communication and collaboration

Social and ethical considerations

Compatibility issues involve ethical and social implications:

• Accessibility- If a new system isnt compatible with assistive technologies, its not inclusive towards those with disability

• Data privacy- Merging data from different systems raises user privacy and data protection concerns

1.1.4 Compare the implementation of systems using a client’s hardware with hosting systems remotely.

Choosing between local hardware and cloud are decisions to be made in consideration of their respective benefits and disadvantages

Cloud computing in itself has 4 main models that it offers:

• Infrastructure as a Service (LaaS)

• Platform as a Service (PasS)

• Software as a Service (SaaS)

• Network as a Service (NaaS)

                                 Cloud computing:                                                    

Pros:                                                                                  Cons:

• Convenience                                                                  -  Security

• Security                                                                          - Service outage

• Backups                                                                         - Storage limits

• Collaboration                                                                  - Slow speeds

• Environmentally friendly                                                 - Limited features   
  

Local computing:

  Pros:                                                                               Cons:

• Security                                                                         - Cost of hardware

• Backups can be controlled                                            - Technical support

• Legacy software                                                            - Lack of collaboration

• Software control

• Feature control

1.1.5 Evaluate alternative installation processes

Types of system installations alongside pros and cons:

Direct- Old system is stopped and new system is started, no overlap.

Parallel- New system is started but old system is kept running alongside it. Data is input into both systems

Pilot- New system is piloted (trialed) in a small part of the business. Once it is running correctly the new system is implemented across the organisation.

Phased- New system is introduced in phases as parts of the old system are gradually replaced with new system

1.1.6 Discuss problems that may arise as a part of data migration

Data migration- Process of moving data from one system to another

Common data migration problems faced:

Incompatible file formats- Different systems may use different file formats that need conversion during migration. Conversion can lead to data loss or corruption if not done carefully

Data structure differences- Data structures define how data is organized within a system. Incompatible structures can make it difficult to import data into new system.

Validation rule issues- Validation rules ensure data accuracy and consistency. Incompatible rules can lead to invalid data within a system.

Incomplete data transfer- Not all data might be transferred successful during migration, leading to missing information in the new system

Internationalization issues:
Data formats- Data formatas for dates, currencies, and measurements can vary internationally. Migration needs to account for these differences to avoid confusion and errors.

Character sets- Different countries use differnece charcter sets to represent text and incompatible character sets can lead to garbled text during migration.

Tips for successful data migration:

Planning- Thoroughly analyze data formats, structures and validation rules in both systems.

Data cleaning- Ensure data is clean and complete before migration to minimise errors

Testing- Test the migration process thoroughly to identify and fix compatiblity issues before full migration.

Internationalization standards- Use international standards for data formats to minimize compatiblity problems.

1.1.7 Suggest various types of testing

Types of testing

Alpha testing- Internal testing process performed by developers and testers who are employees of the organizaiton developing the software. Typically done in a lab environment and not in real world setting

Purpose- To catch bugs that were not discovered during earlier testing phases, focuses on functional correctness, security aspects and software bugs

Process- Involves with box and black box testing techniques and may also include simulated or actual operational testing environments.

Beta testing- Follows alpha testing and involves releasing software to a limited, external group of people outside of organization who test software in real world conditions

Purpose- Primary goal is to obtain feedback from users to identify any potential issues that weren’t caught during internal testing, including usability and compatibility issues as well as validating user experience.

Process- Less controlled and relies on diversity of user base and their environments to uncover unexpected errors

Gamma testing- Less common and typically refers to testing of software that is ready for release or very close to final version. Gamma testing may happen if big changes happen after beta testing.

Purpose- Ensures product readiness for release, particularly after significant late-stage fixes requiring new validation

Process- Like beta testing but less diverse user base and often done internally or very select group of external users.

Other types:
Feedback collection- to gather insights and performance data from users during or after the testing phase, with tools such as direct user reports, automated crash logs or usability surveys

Iterative improvement- Refining of features across rounds of testing feedback.

Test plans consists of 3 parts:

• Details of what is being tested

• Test data to use

• What is expected to happen when test is performed

Three types of test data:

Normal- Data that would be expected to be entered in the system, system should accept it and process it

Extreme- Extreme values are still normal but are at the edges of acceptable and are used to see that the system responds correctly to all normal data.

Abnormal- Data that should NOT be accepted. System should be able to handle this data without crashing or breaking. Validation checks and the handling of exceptions are often used to ensure this data is handled well.

1.1.8 Importance of user documentation

User documentation- Explains how to use each part of a system, acts as a guide of systems features and characteristics. Poor or confusing documentations slows down implementations and increases support needs

The 3 main styles of user documentation:

1.1.9 Methods of providing user documentation

Using a mix of these methods gives users both self service options and direct support when needed.

1.1.10 Methods of delivering user training

Choosing or combining these methods appropriately helps users gain skills efficiently, which directly affects how quickly and successfully a new system is implemented

1.1.11 Causes of data loss

Data loss in system back up is about understanding causes, consequences and prevention methods so systems stay reliable and recoverable

1.1.12 Consequences of data loss

• Loss of critical operational data (e.g. medical records, booking systems) leading to service disruption or unsafe decisions)

• Financial and reputational damage such as cancelled reservations without customers knowing or legal liability for losing records

1.1.13 Methods to prevent data loss

1.1.14 Describe strategies for managing releases and updates

Release stages

Update strategies

Why updates matter:

Performance issues- Not updating can cause slower programs, higher memory/cpu use, crashes and general instability reducing user productivity and system efficiency

Compatibility issues- Diff versions cant always work smoothly together, especially across locations. Outdated clients may struggle to exchange data or use new feature

Security angle- Old versions often have unpatched vulnerabilities, so skipping updates increases risk of malware, data breaches etc.