application engg metrics

8/6/2019 Application Engg Metrics

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APPLICATIONAPPLICATIONENGINEERINGENGINEERING

METRICSMETRICS

HITESHI801031011

ME(SE)- 2ND SEM


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Project-level functions

Reuse DistributionProject-level Return

on InvestmentReusable Code

Percentage

New code

Reused code

Adapted code


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This metrics considers the overall size of the application

produced by the software development project .

Divided into three categories as:

New Code: %age of code developed specifically for the application.

Reused Code, verbatim: %age of code reused verbatim from acorporate reuse library.

Adapted Code: %age of code reused from a corporate reuse library,after adaptation.


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Reuse distribution..

Definition emphasis on:

Size percentage..,, measured in lines of code(LOC). But we can useother measures also, say function points.

Measure is used in computing the percentages, which must beinterpreted with cautions.

Example: Consider a project having

Reused code = 20%

New code = 80%

So, Even if we neglect the cost of integrating the reused code and thenonlinear effects of the software costs, we cannot claim that we have

saved 20% of the development effort, because the size of a reusedasset is larger than the size of the written code if the reusable assetwere not available.


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It quantifies the decision by providing the estimates of risks and benefitsand matching them in an ROI equation.Say, a corporation has a stake that all projects make use of reusable assets,individual projects have to balance the benefits of reuse against other short-term considerations ,like changes in the groups operational procedures ,risks that project staff be distracted by the introduction of reuse technologybut do not benefit from it and overhead caused by producing reusable asset.The decision apply to the software reuse in any one project is notstraightforward i.e. there are some cases where from the projectsviewpoint, the potential risks outweight the benefits.


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This metrics reflects the amount of code contributed by the

individual project to the corporate software reuse library, as apercentage of the size of the application produced by the project.

It can also used to reward the individual projects;

Challenge of the project manager is to optimize this metrics without

undue burden on the project team and without derailing the project

goals.


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II. Domain engineering metrics..

This metrics reflects to what extent the domain engineering effortis successful, by quantifying the level of demand experienced by

domain assets, the level of efficiency of the library and the

degree of usefulness of domain assets.

Software library metrics: To justify the creation or the existence of a softwarereuse library we consider the level of use of the libraries in the organization day

to day operations. We have three metrics to identified the level of library traffic

as:

No. of accesses to the library

No. of retrieval from the library

Library efficiency


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It reflects the corporation involvement in software reuse, or the

corporate maturity w.r.t software reuse .

It includes Productivity Gains ; quantifies the impact of

reuse on corporate operation considering the

distribution of reused and original code in the total

quantity of code produced per unit of time. If the unit of

time is the Year and the amount of code is measuredin KLOC the distribution table is obtained known as

yearly reuse distribution by size as :


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Category Percentage

New code %

Reuse code ,verbatim %

Internal %

External %

Adapted Code %

Internal %

External %


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Reuse Code and Adapted Code , we have

Internal Code : developed in-house

External Code: code acquired from outside source

These two codes having different cost equations and hence weconsidered them separately.

If we ignore the distinction between the internal and external

sources of reusable (or adaptable ) code and in application we

assume that

Cn: New code

Cr: Reusable code

Ca

: Adaptable code


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So, the cost of developing a LOC with reuse averages 0.20 times

the cost of developing a new line from a scratch and the cost of

developing a LOC by adaptation is on average 0.67 times the costof developing a new line from scratch.

We also find that the cost of developing a product with reuse

distribution ( Cn, Cr, Ca ) is a linear function of

having constraints: Cn + Cr+Ca =1 .

We can also use reuse leverage metrics as the ratio between the

productivity of the organization ( LOC/ year ) with reuse over its

productivity without reuse.

Cn +0.2 * Cr +0.67 * Ca


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application engg metrics

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