Week 7 [Fri, Sep 22nd] - Topics

A use case describes an interaction between the user and the system for a specific functionality of the system.

System: Online Banking System (OBS)
Use case: UC23 - Transfer Money
Actor: User
MSS:
  1. User chooses to transfer money.
  2. OBS requests for details of the transfer.
  3. User enters the requested details.
  4. OBS requests for confirmation.
  5. User confirms.
  6. OBS transfers the money and displays the new account balance.
  Use case ends.

    

    


    
    

Extensions:
  3a. OBS detects an error in the entered data.
      3a1. OBS requests for the correct data.
      3a2. User enters new data.
      Steps 3a1-3a2 are repeated until the data entered are correct.
      Use case resumes from step 4.

  3b. User requests to effect the transfer in a future date.
      3b1. OBS requests for confirmation.
      3b2. User confirms future transfer.
      Use case ends.

  *a. At any time, User chooses to cancel the transfer.
      *a1. OBS requests to confirm the cancellation.
      *a2. User confirms the cancellation.
      Use case ends.

    

    


    
    

UML includes a diagram type called use case diagrams that can illustrate use cases of a system visually, providing a visual ‘table of contents’ of the use cases of a system.

In the example on the right, note how use cases are shown as ovals and user roles relevant to each use case are shown as stick figures connected to the corresponding ovals.

Use cases capture the functional requirements of a system.

A use case is an interaction between a system and its actors.

Actors in Use Cases

A use case can involve multiple actors.

An actor can be involved in many use cases.

A single person/system can play many roles.

Many persons/systems can play a single role.

Use cases can be specified at various levels of detail.

While modeling user-system interactions,

• start with high level use cases and progressively work toward lower level use cases.
• be mindful of which level of detail you are working at and not to mix use cases of different levels.

Writing use case steps

Extensions are "add-on"s to the MSS that describe exceptional/alternative flow of events. They describe variations of the scenario that can happen if certain things are not as expected by the MSS. Extensions appear below the MSS.

This example adds some extensions to the use case in the previous example.

System: Online Banking System (OBS)
Use case: UC23 - Transfer Money
Actor: User
MSS:
  1. User chooses to transfer money.
  2. OBS requests for details of the transfer.
  3. User enters the requested details.
  4. OBS requests for confirmation.
  5. User confirms.
  6. OBS transfers the money and displays the new account balance.
  Use case ends.

    

    


    
    

Extensions:
  3a. OBS detects an error in the entered data.
      3a1. OBS requests for the correct data.
      3a2. User enters new data.
      Steps 3a1-3a2 are repeated until the data entered are correct.
      Use case resumes from step 4.

  3b. User requests to effect the transfer in a future date.
      3b1. OBS requests for confirmation.
      3b2. User confirms future transfer.
      Use case ends.

  *a. At any time, User chooses to cancel the transfer.
      *a1. OBS requests to confirm the cancellation.
      *a2. User confirms the cancellation.
      Use case ends.

  *b. At any time, 120 seconds lapse without any input from the User.
      *b1. OBS cancels the transfer.
      *b2. OBS informs the User of the cancellation.
      Use case ends.

    

    


    
    

Note that the numbering style is not a universal rule but a widely used convention. Based on that convention,

• either of the extensions marked 3a. and 3b. can happen just after step 3 of the MSS.
• the extension marked as *a. can happen at any step (hence, the *).

When separating extensions from the MSS, keep in mind that the MSS should be self-contained. That is, the MSS should give us a complete usage scenario.

Also note that it is not useful to mention events such as power failures or system crashes as extensions because the system cannot function beyond such catastrophic failures.

In use case diagrams you can use the <<extend>> arrows to show extensions. Note the direction of the arrow is from the extension to the use case it extends and the arrow uses a dashed line.

You can use actor generalization in use case diagrams using a symbol similar to that of UML notation for inheritance.

In this example, actor Blogger can do all the use cases the actor Guest can do, as a result of the actor generalization relationship given in the diagram.

Do not over-complicate use case diagrams by trying to include everything possible. A use case diagram is a brief summary of the use cases that is used as a starting point. Details of the use cases can be given in the use case descriptions.

Some include ‘System’ as an actor to indicate that something is done by the system itself without being initiated by a user or an external system.

The diagram below can be used to indicate that the system generates daily reports at midnight.

However, others argue that only use cases providing value to an external user/system should be shown in the use case diagram. For example, they argue that view daily report should be the use case and generate daily report is not to be shown in the use case diagram because it is simply something the system has to do to support the view daily report use case.

You are recommended to follow the latter view (i.e. not to use System as a user). Limit use cases for modeling behaviors that involve an external actor.

UML is not very specific about the text contents of a use case. Hence, there are many styles for writing use cases. For example, the steps can be written as a continuous paragraph.

Use cases should be easy to read. Note that there is no strict rule about writing all details of all steps or a need to use all the elements of a use case.

There are some advantages of documenting system requirements as use cases:

• Because they use a simple notation and plain English descriptions, they are easy for users to understand and give feedback.
• They decouple user intention from mechanism (note that use cases should not include UI-specific details), allowing the system designers more freedom to optimize how a functionality is provided to a user.
• Identifying all possible extensions encourages us to consider all situations that a software product might face during its operation.
• Separating typical scenarios from special cases encourages us to optimize the typical scenarios.

One of the main disadvantages of use cases is that they are not good for capturing requirements that do not involve a user interacting with the system. Hence, they should not be used as the sole means to specify requirements.

Software design has two main aspects:

• Product/external design: designing the external behavior of the product to meet the users' requirements. This is usually done by product designers with input from business analysts, user experience experts, user representatives, etc.
• Implementation/internal design: designing how the product will be implemented to meet the required external behavior. This is usually done by software architects and software engineers.

Multi-level design can be done in a top-down manner, bottom-up manner, or as a mix.

• Top-down: Design the high-level design first and flesh out the lower levels later. This is especially useful when designing big and novel systems where the high-level design needs to be stable before lower levels can be designed.
• Bottom-up: Design lower level components first and put them together to create the higher-level systems later. This is not usually scalable for bigger systems. One instance where this approach might work is when designing a variation of an existing system or re-purposing existing components to build a new system.
• Mix: Design the top levels using the top-down approach but switch to a bottom-up approach when designing the bottom levels.

Agile design can be contrasted with full upfront design in the following way:

Agile designs are emergent, they’re not defined up front. Your overall system design will emerge over time, evolving to fulfill new requirements and take advantage of new technologies as appropriate. Although you will often do some initial architectural modeling at the very beginning of a project, this will be just enough to get your team going. This approach does not produce a fully documented set of models in place before you may begin coding. _{-- adapted from agilemodeling.com}

The guiding principle of abstraction is that only details that are relevant to the current perspective or the task at hand need to be considered. As most programs are written to solve complex problems involving large amounts of intricate details, it is impossible to deal with all these details at the same time. That is where abstraction can help.

Data abstraction: abstracting away the lower level data items and thinking in terms of bigger entities

Control abstraction: abstracting away details of the actual control flow to focus on tasks at a higher level

Abstraction can be applied repeatedly to obtain progressively higher levels of abstraction.

Abstraction is a general concept that is not limited to just data or control abstractions.

Coupling is a measure of the degree of dependence between components, classes, methods, etc. Low coupling indicates that a component is less dependent on other components. High coupling (aka tight coupling or strong coupling) is discouraged due to the following disadvantages:

• Maintenance is harder because a change in one module could cause changes in other modules coupled to it (i.e. a ripple effect).
• Integration is harder because multiple components coupled with each other have to be integrated at the same time.
• Testing and reuse of the module is harder due to its dependence on other modules.

In the example below, design A appears to have more coupling between the components than design B.

X is coupled to Y if a change to Y can potentially require a change in X.

Cohesion is a measure of how strongly-related and focused the various responsibilities of a component are. A highly-cohesive component keeps related functionalities together while keeping out all other unrelated things.

Higher cohesion is better. Disadvantages of low cohesion (aka weak cohesion):

• Lowers the understandability of modules as it is difficult to express module functionalities at a higher level.
• Lowers maintainability because a module can be modified due to unrelated causes (reason: the module contains code unrelated to each other) or many modules may need to be modified to achieve a small change in behavior (reason: because the code related to that change is not localized to a single module).
• Lowers reusability of modules because they do not represent logical units of functionality.

Cohesion can be present in many forms. Some examples:

• Code related to a single concept is kept together, e.g. the Student component handles everything related to students.
• Code that is invoked close together in time is kept together, e.g. all code related to initializing the system is kept together.
• Code that manipulates the same data structure is kept together, e.g. the GameArchive component handles everything related to the storage and retrieval of game sessions.

In terms of timing and frequency, there are two general approaches to integration: late and one-time, early and frequent.

Late and one-time: wait till all components are completed and integrate all finished components near the end of the project.

Early and frequent: integrate early and evolve each part in parallel, in small steps, re-integrating frequently.

Big-bang integration: integrate all components at the same time.

Incremental integration: integrate a few components at a time. This approach is better than big-bang integration because it surfaces integration problems in a more manageable way.

A milestone is the end of a stage which indicates significant progress. You should take into account dependencies and priorities when deciding on the features to be delivered at a certain milestone.

In some projects, it is not practical to have a very detailed plan for the whole project due to the uncertainty and unavailability of required information. In such cases, you can use a high-level plan for the whole project and a detailed plan for the next few milestones.

A buffer is time set aside to absorb any unforeseen delays. It is very important to include buffers in a software project schedule because effort/time estimations for software development are notoriously hard. However, do not inflate task estimates to create hidden buffers; have explicit buffers instead. Reason: With explicit buffers, it is easier to detect incorrect effort estimates which can serve as feedback to improve future effort estimates.

Keeping track of project tasks (who is doing what, which tasks are ongoing, which tasks are done etc.) is an essential part of project management. In small projects, it may be possible to keep track of tasks using simple tools such as online spreadsheets or general-purpose/light-weight task tracking tools such as Trello. Bigger projects need more sophisticated task tracking tools.

Issue trackers (sometimes called bug trackers) are commonly used to track task assignment and progress. Most online project management software such as GitHub, SourceForge, and BitBucket come with an integrated issue tracker.

A screenshot from the Jira Issue tracker software (Jira is part of the BitBucket project management tool suite):

A Work Breakdown Structure (WBS) depicts information about tasks and their details in terms of subtasks. When managing projects, it is useful to divide the total work into smaller, well-defined units. Relatively complex tasks can be further split into subtasks. In complex projects, a WBS can also include prerequisite tasks and effort estimates for each task.

The effort is traditionally measured in man hour/day/month i.e. work that can be done by one person in one hour/day/month. The Task ID is a label for easy reference to a task. Simple labeling is suitable for a small project, while a more informative labeling system can be adopted for bigger projects.

All tasks should be well-defined. In particular, it should be clear as to when the task will be considered done.

A Gantt chart is a 2-D bar-chart, drawn as time vs tasks (represented by horizontal bars).

A sample Gantt chart:

In a Gantt chart, a solid bar represents the main task, which is generally composed of a number of subtasks, shown as grey bars. The diamond shape indicates an important deadline/deliverable/milestone.

Given below are three commonly used team structures in software development. Irrespective of the team structure, it is a good practice to assign roles and responsibilities to different team members so that someone is clearly in charge of each aspect of the project. In comparison, the ‘everybody is responsible for everything’ approach can result in more chaos and hence slower progress.

Egoless team

In this structure, every team member is equal in terms of responsibility and accountability. When any decision is required, consensus must be reached. This team structure is also known as a democratic team structure. This team structure usually finds a good solution to a relatively hard problem as all team members contribute ideas.

However, the democratic nature of the team structure bears a higher risk of falling apart due to the absence of an authority figure to manage the team and resolve conflicts.

Chief programmer team

Frederick Brooks proposed that software engineers learn from the medical surgical team in an operating room. In such a team, there is always a chief surgeon, assisted by experts in other areas. Similarly, in a chief programmer team structure, there is a single authoritative figure, the chief programmer. Major decisions, e.g. system architecture, are made solely by him/her and obeyed by all other team members. The chief programmer directs and coordinates the effort of other team members. When necessary, the chief will be assisted by domain specialists e.g. business specialists, database experts, network technology experts, etc. This allows individual group members to concentrate solely on the areas in which they have sound knowledge and expertise.

The success of such a team structure relies heavily on the chief programmer. Not only must he/she be a superb technical hand, he/she also needs good managerial skills. Under a suitably qualified leader, such a team structure is known to produce successful work.

Strict hierarchy team

At the opposite extreme of an egoless team, a strict hierarchy team has a strictly defined organization among the team members, reminiscent of the military or a bureaucratic government. Each team member only works on his/her assigned tasks and reports to a single “boss”.

In a large, resource-intensive, complex project, this could be a good team structure to reduce communication overhead.

In the forking workflow, the 'official' version of the software is kept in a remote repo designated as the 'main repo'. All team members fork the main repo and create pull requests from their fork to the main repo.

To illustrate how the workflow goes, let’s assume Jean wants to fix a bug in the code. Here are the steps:

1. Jean creates a separate branch in her local repo and fixes the bug in that branch.
   Common mistake: Doing the proposed changes in the master branch -- if Jean does that, she will not be able to have more than one PR open at any time because any changes to the master branch will be reflected in all open PRs.
2. Jean pushes the branch to her fork.
3. Jean creates a pull request from that branch in her fork to the main repo.
4. Other members review Jean’s pull request.
5. If reviewers suggested any changes, Jean updates the PR accordingly.
6. When reviewers are satisfied with the PR, one of the members (usually the team lead or a designated 'maintainer' of the main repo) merges the PR, which brings Jean’s code to the main repo.
7. Other members, realizing there is new code in the upstream repo, sync their forks with the new upstream repo (i.e. the main repo). This is done by pulling the new code to their own local repo and pushing the updated code to their own fork. If there are unmerged branches in the local repo, they can be updated too e.g., by merging the new master branch to each of them.
   Possible mistake: Creating another 'reverse' PR from the team repo to the team member's fork to sync the member's fork with the merged code. PRs are meant to go from downstream repos to upstream repos, not in the other direction.

One main benefit of this workflow is that it does not require most contributors to have write permissions to the main repository. Only those who are merging PRs need write permissions. The main drawback of this workflow is the extra overhead of sending everything through forks.

You can follow the steps in the simulation of a forking workflow given below to learn how to follow such a workflow.

This activity is best done as a team.

Step 1. One member: set up the team org and the team repo.

1. Create a GitHub organization for your team, if you don't have one already. The org name is up to you. We'll refer to this organization as team org from now on.

2. Add a team called developers to your team org.

3. Add team members to the developers team.

4. Fork se-edu/samplerepo-workflow-practice to your team org. We'll refer to this as the team repo.

5. Add the forked repo to the developers team. Give write access.

Step 2. Each team member: create PRs via own fork.

1. Fork that repo from your team org to your own GitHub account.

2. Create a branch named add-{your name}-info (e.g. add-johnTan-info) in the local repo.

3. Add a file yourName.md into the members directory (e.g., members/jonhTan.md) containing some info about you into that branch.

4. Push that branch to your fork.

5. Create a PR from that branch to the master branch of the team repo.

Step 3. For each PR: review, update, and merge.

1. [A team member (not the PR author)] Review the PR by adding comments (can be just dummy comments).

2. [PR author] Update the PR by pushing more commits to it, to simulate updating the PR based on review comments.

3. [Another team member] Approve and merge the PR using the GitHub interface.

4. [All members] Sync your local repo (and your fork) with upstream repo. In this case, your upstream repo is the repo in your team org.

   • The basic mechanism for this has two steps (which you can do using Git CLI or any Git GUI):
     (1) First, pull from the upstream repo -- this will update your clone with the latest code from the upstream repo.
     If there are any unmerged branches in your local repo, you can update them too e.g., you can merge the new master branch to each of them.
     (2) Then, push the updated branches to your fork. This will also update any PRs from your fork to the upstream repo.
   • Some alternatives mechanisms to achieve the same can be found in this GitHub help page.
     If you are new to Git, we recommend that you use the above two-step mechanism instead, so that you get a better view of what's actually happening behind the scene.

Step 4. Create conflicting PRs.

1. [One member]: Update README: In the master branch, remove John Doe and Jane Doe from the README.md, commit, and push to the main repo.

2. [Each team member] Create a PR to add yourself under the Team Members section in the README.md. Use a new branch for the PR e.g., add-johnTan-name.

Step 5. Merge conflicting PRs one at a time. Before merging a PR, you’ll have to resolve conflicts.

1. [Optional] A member can inform the PR author (by posting a comment) that there is a conflict in the PR.

2. [PR author] Resolve the conflict locally:

   1. Pull the master branch from the repo in your team org.
   2. Merge the pulled master branch to your PR branch.
   3. Resolve the merge conflict that crops up during the merge.
   4. Push the updated PR branch to your fork.

3. [Another member or the PR author]: Merge the de-conflicted PR: When GitHub does not indicate a conflict anymore, you can go ahead and merge the PR.

RCS can be done in two ways: the centralized way and the distributed way.

Centralized RCS (CRCS for short) uses a central remote repo that is shared by the team. Team members download (‘pull’) and upload (‘push’) changes between their own local repositories and the central repository. Older RCS tools such as CVS and SVN support only this model. Note that these older RCS do not support the notion of a local repo either. Instead, they force users to do all the versioning with the remote repo.

The centralized RCS approach without any local repos (e.g., CVS, SVN)

Distributed RCS (DRCS for short, also known as Decentralized RCS) allows multiple remote repos and pulling and pushing can be done among them in arbitrary ways. The workflow can vary differently from team to team. For example, every team member can have his/her own remote repository in addition to their own local repository, as shown in the diagram below. Git and Mercurial are some prominent RCS tools that support the distributed approach.

The decentralized RCS approach