Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi

Lecture 9 A system is identified in terms of the single goal it is to achieve. A system name is a cognitive handle that allows the identification and communication of a particular coherent and purposeful set of activities. A system name is usually presented in the form of: “A system to do/be/achieve X” Example: A system to generate birth certificates A system to generate reusable components A system to provide a uniform computing platform across government agencies All these may actually refer to the same application software! System

Lecture 9 Software Development is a form of System Development System Development entails the processes of: Finding out what is the problem Arriving at a solution Delivering on a good solution Discovery Invention Construction

Lecture 9 Analysis Design Implementation So “analysis and design” is all about identifying what the problem is and to propose one or several solutions to rectify the problem. What is the problem? What is a solution? How do we deliver on a good solution? Discovery Invention Construction

Lecture 9 Figuring out the problem. The problem that is to be figured out is immersed in the real world. The real world (the problem situation) is a web of interactions of amazing complexity To have a chance, we need to be able to focus only on what is: RELEVANT

Lecture 9 We need therefore to concentrate on: Those elements about which we need to ask questions, Those elements about which we need to answer questions We also need to make sure that: Only those elements that are of our direct and immediate concern are focused on at any one time.

Lecture 9 The first of these is called: The second is called: CONTEXTUALIZATION ABSTRACTION

Lecture 9 Once we have understood the problem, we need to: Communicate our understanding: To ourselves at a later time To others To do so, we need to capture, retain and communicate what is relevant and in context. This is called Modeling

Lecture 9 Modeling is therefore a fundamental element of analysis and as such a vital part of software development. In order to capture, retain and communicate what is needed, the modeler has to use a language. This is called: The Modeling Language The modeling language has to contain the vocabulary and the grammar of the modeling approach utilized.

Lecture 9 What’s there? How does it happen? When does it happen? (or in what sequence?) Things and static relationships Change Order and timing of change

Lecture 9 Things and static relationships Change Order and timing of change Structure Transformations Causal (sequential) relationships For all deterministic systems we must capture all that is relevant of these three aspects, if we are to have sufficient understanding of them.

Lecture 9 System Modeling In SE, we have an array of notations and diagrams for modeling in each of these three views. Structure Modeling Entity Relationship Diagrams, Formal Structural Models (e.g. Z, Object Z or VDM), Class Diagrams,… Transformational Modeling Transformational Relations(Functional Specification), Activity Diagrams, Data Flow Diagrams (with specification), Flow Charts, … Causal (Dynamic) Modeling Sequence Diagrams, Collaboration Diagrams, State-charts (State Transition Diagrams), Petri-nets, Entity Life Histories,…

Lecture 9 Structure modeling is modeling of things and their situational relationships. A photograph is a good structure model. It shows things that were there when the picture was taken and how they were situated with respect to one another. We can similarly compose diagrams or other models of a problem situation in which we depict all the relevant things and relationships. There are many ways to do this. We shall discuss the three most popular and prevalent of these. Namely: Entity Relationship Modeling which is used mainly for database design Formal Schemas and Formal Object Schemas (using Z and Object Z) Class Diagrams (using UML) used mainly as part of object oriented modeling Structure Modeling

Lecture 9 Entity Relationship (ER) Modeling: This is an informal (or semi-formal) approach to structure modeling in which a situation is studied so that static and persistent elements in it are identified, along with their static relationships. A collection of like elements is called an entity. A mapping of elements of one entity onto another entity (or itself) is called a relationship. Entities are defined in terms of a name and a set of attributes. Relationships are defined in terms of a verb phrase (e.g. works-for) that establishes the nature of the mapping between the entities. The results of ER modeling are almost always shown using diagrams. There are many different conventions. In the absence of an industry standard, we use a popular one here of my preference. Structure Modeling

Lecture 9 Example: Employee Name: SSN: Salary: Department Name: Location: Budget: Works-For m 1 This means that there are many elements belonging to the set Employee (i.e. many persons employed) each is mapped into (has a relationship with) only one element belonging to the entity Department (a specific department). The relationship is that this particular employee works for one specific department. For each employee we keep his or her name, social security number and current salary. For each department we keep the name of the department, its location and its budget. You have already learned this modeling approach earlier in the course. Structure Modeling

Lecture 9 Formal Object Schemas: Object Z Stack[T] max : N items: seq T #items  max INIT items = ‹ › Push  ( items) #items < max items’ = ‹ item? › ⁀ items item?:T Structure Modeling

Lecture 9 Pop  ( items) item!  ‹ › items = ‹ item! › ⁀ items’ item!:T top  ( items) item!  ‹ › items’ = items item!:T Structure Modeling

Lecture 9 There are many different approaches to causal modeling. Whilst they all attempt to do the same thing, they are not all of the same level of capability, formality, ease of use or learnability. In this course we cover a number of popular approaches to causal modeling, including: Entity Life Histories The UML suite of dynamic modeling facilities, which include Petri-nets Sequence diagrams Collaboration diagrams State diagrams Causal Modeling

Lecture 9 Entity Life Histories These are diagrams that depict the various states of a class or type of object from inception to demise. Usually used in relation to persistent database “entities”, they can become overwhelmed if the states are too numerous or the object can possess concurrent states. They also do not necessarily depict the events that lead to state transitions. EMP CREATE INIT UPDATE REPORT RETIRE ARCHIVE * * Causal Modeling

Lecture 9 Transformation modeling is the third modeling view. It answers the question “how”. Depending on level of granularity there are many techniques. Including: Abstraction Level: Dataflow Diagrams Activity Diagrams Low Level: Pseudo-code Flowcharts etc. Not part of UML Transformational Modeling

Lecture 9 Flow charts Flow charts depict the flow of control. They show how operations are performed and decisions made by depicting how the control in the program is exchanged from the beginning to the end of all paths of interest. Flow charts show how the program works. Flow charts are composed of a number of node types and one type of arc. The node types are: Start/End nodeTransformation nodeDecision node Link nodeSpecial processing nodesLogic nodes Transformational Modeling

Lecture 9 Flow charts can be high level or low level High level flow charts depict the flow of control at a high level of granularity, such as the organization or the entire system. Low level ones usually depict the flow of control in a specific program unit. The difference between a high level and low level flow chart is that in a low level flow chart all transformational nodes contain transformations that can not be usefully broken down to simpler flowcharts themselves. By this we mean doing so would produce transformation at a lower level of granularity than that of the target programming language. Transformational Modeling

Lecture 9 Flow chart nodes: Start/End nodes: These mark the beginning and end of a flow within a flowchart Transformation nodes: These show a logical step taken Terminator Transformation Alternate transformation Manual transformation Transformational Modeling

Lecture 9 Decision nodes: These show alternate conditions or paths the flow may take Link nodes: These connect various parts of the diagram (e.g. continue on next page) Logic nodes: These are logical operators such as AND, OR and NOT Condition AND OR NOT On page connector Off page connector Transformational Modeling

Lecture 9 Special processing nodes: These are nodes that depict specific large scale processing or machine interaction. Useful in the early days when flowcharting was amongst the only modeling methods available, they are now largely disused. Manual input Disk Other mag. storage Stored data Punched tape Punched card Seq. Access device Console or display Extract Merge Sort Collate Internal storage Delay Transformational Modeling

Lecture 9 Start End Read N N>0 T F Read A,B A=A+B N=N-1 N=0 F T Write A Transformational Modeling

Lecture 9 Data Flow Diagrams Data flow diagrams depict the flow of data. They show how data received as input is changed to outputs by the various operations performed. Data flow diagrams show how the data changes. Basic data flow diagrams are composed of a number of node types and one type of arch. The node types are: External Entities (Sources and Sinks)Processing node Data-storesLink nodes Transformational Modeling

Lecture 9 External entities (sources and Sinks): These are entities outside the scope of our focus that provide the inputs from the outside or receive the outputs generated. They are labeled by a noun or an object or class name. Process nodes: These depict the processing that is done to the inputs into that process to form the output. Usually these nodes are labeled by a verb phrase representing the nature of the processing to be done and a number sequence depicting the process and its level Customer Book seat Transformational Modeling

Lecture 9 Data-stores: These are buffers where interim outputs generated are stored for future usage. Data-stores are usually named. Link nodes: They connect the various parts of the diagrams to yield a less cluttered result. They are usually numbered or carry a symbol. Primary Buffer The only arc is called a dataflow and it depicts the flow of data (as input into or output from) an external entity or process. They are usually named. client address 22 Transformational Modeling

Lecture 9 Example DFD Validate Sell Prepare SX Transaction Register Transaction Account Invalid Req. Advice Transaction Advice Sell Validation Trans. Confirmation Sell Details Account Update Sell Advice No. of Stock owned Account Sell Market Stock Price Sell Stock; Level 3 Transformational Modeling

Lecture 9 Data Flow diagrams may depict a situation at multiple levels of granularity. By that we mean a process in a data flow diagram may be decomposed into an entire new dataflow diagram at a lower level, and so on. At each lower level, there will be more detail of the model visible. Conversely, one can say that a higher level process can be described in terms of a dataflow diagram composed of simpler, lower level processes, data flows and data-stores. However this decomposition process must stop at some stage. At that stage we shall still have a dataflow diagram that only depicts the transformation of inputs to outputs of various processes. It however does not say HOW each leaf level process should achieve this. This may be obvious but is not defined. Transformational Modeling

Lecture 9 Dataflow diagrams are more so a mechanism for abstraction than a transformational modeling technique. They must be accompanied by a complementary mechanism that defines the leaf level transformations. Something like a flowchart of each leaf process, a pseudo-code, mathematical equation, truth table or formal definition is needed. Important Note: Transformational Modeling

Lecture 9 Pseudo-code: begin Read r,a; Declare x,y; if { (a) L.T. 0 a=(-1)*a; }; Set x to r*sin(a); Set y to r*cos(a); Write x; Write y; end Convert to Cartesian r a x y Transformational Modeling

Lecture 9 Mathematical expression: Convert to Cartesian r a x y Desc. For Transformational Modeling

Lecture 9 Activity diagrams depict the processing aspects of the system. They are similar to flowcharts except: ACTIVITY DIAGRAMS Activity charts allow synchronization They are similar to dataflow diagrams except: Transition between activities is via conditions not data. Activity charts allow synchronization Transformational Modeling

Lecture 9 Order Processing Finance Receive Order Receive Supply Select Outstanding order item Assign Goods to Order Assign Item to Order Reorder Item Add Remainder to Stock Check Line Item Cancel Order Check order Authorize payment [failed] [succeeded] Dispatch Order [Stock assigned to all line items and payment authorized] *[for each line item on order] * [for each chosen order item] [in stock] [all outstanding order items filled] [notify supply] [out of stock] Stock Manager Transformational Modeling

Lecture 9 Structure TransformationCausality Objects Classes Relationships Inputs Outputs Transformations Events States Sequences ENCAPSULATION

Lecture 9 UML has a an array of notations and diagrams for modeling in each of these three views. Structure Modeling Class notation, object notation, Associations, Links, Class diagrams, object diagrams,… Transformational Modeling Actors, Transformational relations, Use Case diagrams, Context Diagrams, Activity diagrams,Transformational definitions, …

Lecture 9 Causal (Dynamic) Modeling Events, Activities, Actions, Transitions, States, Sequence diagrams, Collaboration diagrams, Statechart diagrams, etc.… In the next session we shall start with structural modeling and introduce some important elements of the UML notation set.