Week 7 [Sep 30] - Topics

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

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 below, 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 at which level of details you are working on 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. OBS transfers the money and displays the new account balance.
  6. Use case ends.


• Extensions:
  1. 3a. OBS detects an error in the entered data.
     1. 3a1. OBS requests for the correct data.
     2. 3a2. User enters new data.
     3. Steps 3a1-3a2 are repeated until the data entered are correct.
     4. Use case resumes from step 4.
     
     
  2. 3b. User requests to effect the transfer in a future date.
     1. 3b1. OBS requests for confirmation.
     2. 3b2. User confirms future transfer.
     3. Use case ends.
     
     
  3. *a. At any time, User chooses to cancel the transfer.
     1. *a1. OBS requests to confirm the cancellation.
     2. *a2. User confirms the cancellation.
     3. Use case ends.
     
     
  4. *b. At any time, 120 seconds lapse without any input from the User.
     1. *b1. OBS cancels the transfer.
     2. *b2. OBS informs the User of the cancellation.
     3. 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.

We recommend that you 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 does 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 the 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.

The guiding principle of abstraction is that only details that are relevant to the current perspective or the task at hand needs 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 abstractions.

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 a 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.

class Foo{
    ...
    new Bar().read();
    ...
}

class Bar{
    void read(){
        ...
    }
    
    void write(){
        ...
    }
}

Some examples of different coupling types:

• Content coupling: one module modifies or relies on the internal workings of another module e.g., accessing local data of another module
• Common/Global coupling: two modules share the same global data
• Control coupling: one module controlling the flow of another, by passing it information on what to do e.g., passing a flag
• Data coupling: one module sharing data with another module e.g. via passing parameters
• External coupling: two modules share an externally imposed convention e.g., data formats, communication protocols, device interfaces.
• Subclass coupling: a class inherits from another class. Note that a child class is coupled to the parent class but not the other way around.
• Temporal coupling: two actions are bundled together just because they happen to occur at the same time e.g. extracting a contiguous block of code as a method although the code block contains statements unrelated to each other

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 many modules may need to be modified to achieve a small change in behavior (reason: because the code realated 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.

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 variations 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}

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

Based on the order in which components are integrated, incremental integration can be done in three ways.

Top-down integration: higher-level components are integrated before bringing in the lower-level components. One advantage of this approach is that higher-level problems can be discovered early. One disadvantage is that this requires the use of stubs in place of lower level components until the real lower-level components are integrated to the system. Otherwise, higher-level components cannot function as they depend on lower level ones.

Bottom-up integration: the reverse of top-down integration. Note that when integrating lower level components, drivers may be needed to test the integrated components because the UI may not be integrated yet, just like top-down integration needs stubs.

Sandwich integration: a mix of the top-down and the bottom-up approaches. The idea is to do both top-down and bottom-up so as to 'meet' in the middle.

A milestone is the end of a stage which indicates a significant progress. We 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, we can use a high-level plan for the whole project and a detailed plan for the next few milestones.

A buffer is a 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 is 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 a 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 track tasks using simple tools as online spreadsheets or general-purpose/light-weight tasks 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.

PERT (Program Evaluation Review Technique) chart uses a graphical technique to show the order/sequence of tasks. It is based on a simple idea of drawing a directed graph in which:

• Node or vertex captures the effort estimation of a task, and
• Arrow depicts the precedence between tasks

A PERT chart can help determine the following important information:

• The order of tasks. In the example above, Final Testing cannot begin until all coding of individual subsystems have been completed.
• Which tasks can be done concurrently. In the example above, the various subsystem designs can start independently once the High level design is completed.
• The shortest possible completion time. In the example above, there is a path (indicated by the shaded boxes) from start to end that determines the shortest possible completion time.
• The Critical Path. In the example above, the shortest possible path is also the critical path.

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 expert, network technology expert, etc. This allows individual group members to concentrate solely on the areas where they have sound knowledge and expertise.

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

Strict hierarchy team

In 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 bureaucratic government. Each team member only works on his 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 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.
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.

This activity is best done as a team. If you are learning this alone, you can simulate a team by using two different browsers to log into GitHub using two different accounts.

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

   • Create a GitHub organization for your team. The org name is up to you. We'll refer to this organization as team org from now on.
   • Add a team called developers to your team org.
   • Add your team members to the developers team.
   • Fork se-edu/samplerepo-workflow-practice to your team org. We'll refer to this as the team repo.
   • Add the forked repo to the developers team. Give write access.

2. Each team member: create PRs via own fork

   • Fork that repo from your team org to your own GitHub account.
   • Create a PR to add a file yourName.md (e.g. jonhDoe.md)  containing a brief resume of yourself (branch → commit → push → create PR)

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

   • A team member (not the PR author): Review the PR by adding comments (can be just dummy comments).
   • PR author: Update the PR by pushing more commits to it, to simulate updating the PR based on review comments.
   • Another team member: Merge the PR using the GitHub interface.
   • 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.

4. Create conflicting PRs.

   • Each team member: Create a PR to add yourself under the Team Members section in the README.md.
   • One member: in the master branch, remove John Doe and Jane Doe from the README.md, commit, and push to the main repo.

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

   • [Optional] A member can inform the PR author (by posting a comment) that there is a conflict in the PR.
   • PR author: Pull the master branch from the repo in your team org. Merge the pulled master branch to your PR branch. Resolve the merge conflict that crops up during the merge. Push the updated PR branch to your fork.
   • Another member or the PR author: 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.

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.

Feature branch workflow is similar to forking workflow except there are no forks. Everyone is pushing/pulling from the same remote repo. The phrase feature branch is used because each new feature (or bug fix, or any other modification) is done in a separate branch and merged to master branch when ready.

The centralized workflow is similar to the feature branch workflow except all changes are done in the master branch.