Know-Cap: A Method for Knowledge Capitalization in Software

Engineering

Gislaine Camila Lapasini Leal

1,2

, Paulo Cezar Stadzisz

and Elisa Hatsue M. Huzita

CPGEI, Federal Technological University of Parana, Curitiba, Paran

a, Brazil

Department of Production Engineering, State University of Maring

a, Maring

a, Paran

a, Brazil

Department of Computing, State University of Maring

a, Maring

a, Paran

a, Brazil

1 STAGE OF THE RESEARCH

The research is in the design phase of the capitaliza-

tion method. At the moment the steps, activities and

guidelines for the capitalization of knowledge in Soft-

ware Engineering were deﬁned. It is named Know-

Cap method.

The Figure 1 shows a conceptual model of the

Know-Cap method. The faces of the prism repre-

sent the source for obtain knowledge (people) and

the steps of the method (Identify, Add Value, Main-

tain and Monitor). As it can be seen in Figure 1, the

people is the base of the capitalization method. The

representation emphasizes that people is the base of

the capitalization process, since they hold, use and

generate knowledge throughout the software develop-

ment. In addition, they participate in identifying the

knowledge demands. The step Monitor acts as an in-

tegrator by allowing the monitoring of the evolution

of knowledge, by identifying its obsolescence and/or

valuation.

Figure 1: Know-Cap.

Also, analyzing Figure 1 it is possible to observe

by means of two-way arrows, the Know-Cap method

is iterative. It enables to reﬁne the artifacts and obtain

feedback in relation to the demands and the knowl-

edge development.

The proposal of Know-Cap was guided by the fol-

lowing assumptions:

• Prescriptive: the method provides guidelines

for the implementation of activities, highlighting

what should be done and how. Were also de-

ﬁned templates for the generated artifacts, en-

abling standardization and formal way to commu-

nicate.

• Focused on the core areas of software engi-

neering: the method highlights the conversion

of knowledge into organizational assets related

to Requirements, Design and Implementation

stages. Independence from the development

methodology: the method may be used regardless

of the approach used in the development, being it

traditional or agile. However, it is noteworthy that

the methodology inﬂuences the amount of knowl-

edge that is capitalized. For example, the artifacts

deﬁned by templates waterfall and RUP promote

the materialization of knowledge, ie, assist in the

process of outsourcing. On the other hand, the

shorter iterations and continuous planning of agile

methods facilitate the sharing of tacit knowledge,

ie socialization.

• Independence of company size: the method can

be adopted by companies of any size, regardless

of project or team size.

For Know-Cap adoption should be considered the

involvement of top management, deﬁnition of a team

responsible for selection of a pilot project. Support

from top management is essential to ensure the nec-

essary resources to capitalize knowledge. The team

responsible must involve at least one employee in

each area (Requirements, Design and Implementa-

tion). Team members will be responsible for promot-

ing the activities funded.

Camila Lapasini Leal G., Cezar Stadzisz P. and Huzita E. (2013).

Know-Cap: A Method for Knowledge Capitalization in Software Engineering.

In Doctoral Consortium, pages 28-36

 SCITEPRESS

The effectiveness of capitalization depends on or-

ganizational policies, strategies and managerial and

cultural aspects, not just the method itself.

The following sections describe the steps that

comprise the method.

1.1 Identify

It is a strategic step that aims to identify the demands

of knowledge and its importance to aid decision mak-

ing and support the organization’s processes. This

step should involve the largest number of participants

(project manager, developers, analysts, and others), as

the other directs. The activities of this step, namely:

identifying knowledge gaps, analyze the knowledge

demands, knowledge selection, identify the location

and knowledge classifying.

Identify Gaps in knowledge it is a planning ac-

tivity in which the demands of knowledge must be

identiﬁed. It is important to involve all stakeholders in

the process, since this activity will guide the remain-

ing steps of the capitalization of knowledge and en-

able direct efforts. To identify these gaps can be used

techniques, such as interviews, SWOT (Strengths,

Weaknesses, Opportunities, Threats), brainstorming

and benchmarking.

Analyze the Demands of Knowledge aims to

map who are interested, potential beneﬁts and avail-

ability of each knowledge identiﬁed. The sources for

obtaining knowledge can be internal or external to the

organization and include training, consulting, work-

shops and technical visits.

Select Knowledge involves identifying what are

the critical knowledge, ie knowledge that has greater

value for the organization. (Kokkoniemi and Harju-

maa, 2009) emphasize that it is virtually impossible

to collect and record all the knowledge involved in

an organization, regardless of its size. Due to con-

straints of time and cost it is not possible to capital-

ize on all the knowledge involved in the activities, so

must be selected the skills that enable higher returns.

The knowledge selection can be made from the fol-

lowing elements: the experience of the project man-

ager and team, historical project data, expert judg-

ment or based on the requirements of the maturity

model CMMI (Capability Maturity Model Integra-

tion). Other factors that may assist in the knowledge

selection is the risk analysis of loss and identifying

key areas of knowledge.

Identify the Location is to determine where the

explicit knowledge is embodied (artifact, document,

tool). Regarding tacit knowledge is necessary to iden-

tify the people in the organization who has it. Where

knowledge is not available in the organization the

mechanisms of skilled labor acquisition or training

can be used.

Classify the Knowledge is an activity that aims

to organize the knowledge and thus, facilitate their re-

covery, dissemination and access. The classiﬁcation

allows standardizing the vocabulary and, thus estab-

lishing a standard language for interaction and shar-

ing of knowledge and experiences, which minimizes

communication problems. The categories deﬁned in

Know-Cap for the knowledge classiﬁcation are:

• Domain Knowledge: refers to the speciﬁc knowl-

edge of the application domain, ie, the business

rules.

• Process Knowledge: refers to knowledge about

the structure of the work, including the deﬁnition

of responsibilities and tasks.

• Resources Knowledge: includes knowledge about

the technical resources (tools such as case tools,

version control tools, project management tools,

development environment) and non-technical re-

sources (human resources) used.

• Technology Knowledge: involves knowledge re-

lated to norms, standards, approaches, program-

ming language, database, frameworks and others.

• Technical Knowledge: refers to the ﬁnal products

and by products generated.

• Management Knowledge: refers to knowledge of

planning, monitoring and conducting the project.

1.2 Add Value

The purpose of this step is to increase the value of

knowledge and it occurs through the use, exploitation

and reuse them. The step involves the following activ-

ities: explicit, appraise, disseminate, instantiate and

update knowledge.

Explicit Knowledge refers to the externalization

of tacit knowledge identiﬁed. The knowledge con-

version can be performed by interviews, observation,

brainstorming, and others. These techniques consti-

tute the ﬁrst step for the externalization. They are

informal approaches in which the terms are not pre-

cisely deﬁned. As a way to support knowledge ex-

plicitness can be used the following practices:

• Deﬁne a glossary of terms related to the applica-

tion domain.

• Formalize the good practices of coding, identify-

ing the language to be adopted during implemen-

tation, variable naming, functions naming, con-

stant naming, comments, indentation and others.

It is a knowledge that facilitates the integration of

new team members.

Know-Cap:AMethodforKnowledgeCapitalizationinSoftwareEngineering

• Document lessons learned, keeping track of what

has occurred and an analysis of causes. The

lessons learned can be identiﬁed in each of the

steps (Requirements, Design and Implementa-

tion) and shall include all types of experiences,

not just the successful results.

• Develop rationale recording founded problems,

decisions made, alternatives considered, criteria

and arguments that led to the decision. (Dutoit

and Paech, 2000) and (Gueraich and Boufada,

2011) indicate that this type of initiative intro-

duces an initial workload. However, it is benef-

ical to support decision making in the later stages,

usually, as well as new projects.

• Document change requests. It is an activity

that make possible track changes and maintaining

traceability, ie, monitoring the generated artifacts.

• Prepare documents for inspection. It is an ac-

tivity connected to each stage of development

that allows to acquire and reuse knowledge

(Kokkoniemi, 2006).

Value the Knowledge consists in measuring the

value of each asset of knowledge. It is noteworthy

that the value of knowledge is not static, it evolves

with time, circumstances and priorities. That is, the

knowledge value can be increased (increase) or decre-

mented (depreciation) over time. To establish the

knowledge value can be used techniques of activity-

based costing method or cost centers.

Disseminate the Knowledge involves deﬁning

who are interested in every kind of knowledge and

establish appropriate mechanisms for knowledge dis-

tribution. Strategies for dissemination of knowledge

must consider the several perspectives on the impor-

tance of each knowledge category (Figure 2). This

perception impacts the extent to which knowledge is

required and also the perception of its value.

Figure 2: Knowledge category.

Instantiate the Knowledge is to apply the knowl-

edge in problem solving and decision making. The

knowledge reuse is an activity that adds value, ie mon-

etize knowledge. It is the activity in which the return

on investment is generated. The reuse of knowledge

allows to avoid rework and supports in solving recur-

ring problems, which allows to obtain improvements

in the quality and productivity.

Update Knowledge involves the modiﬁcation of

knowledge from experience. Aims at the maintenance

of knowledge, that is, keep them updated to allow the

reuse.

1.3 Maintain

It is a step that aims to preserve the knowledge ac-

quired. This stage involves the following activities:

represent and store of knowledge.

Representing involves modeling formally the

knowledge to enable effective understanding, com-

munication and facilitate the reuse. The formal rep-

resentation of knowledge can be performed using

the following techniques: logic, taxonomy, ontology,

frames, semantic networks and other

Store is the activity that allows retain knowledge

so that it can be distributed and reused.

1.4 Monitor

It is a step that aims to establish continuous coordina-

tion among the remaining steps, evaluate the results,

monitor the dynamics of knowledge and provide feed-

back for reﬁnement of crucial knowledge. The met-

rics permit to quantify the objectives and reﬂect in the

performance. The Know-Cap presents an initial set of

metrics that allow monitoring, evaluation and under-

standing of the corporation knowledge.

2 OUTLINE OF OBJECTIVES

The main goal is to specify a method for capital-

ize knowledge in software engineering. The speciﬁc

goals are to:

• Identify the categories and knowledge involved in

Software Engineering;

• Deﬁne strategies to select the crucial knowledge;

• Deﬁne strategies to value the crucial knowledge;

• Specify the method of capitalization of knowl-

edge, identifying their steps, guidelines and tech-

niques that can be used;

• Representing the method appropriately to enable

effective communication and understanding its;

IC3K2013-DoctoralConsortium

• Evaluate the proposed method by conducting mul-

tiple case studies and experimental studies;

• Reﬁne the proposed method.

3 RESEARCH PROBLEM

The software production is a knowledge-intensive ac-

tivity, where prevail the cognitive activities. So,

knowledge is an important factor for production. The

main assets involved in software development is the

intellectual capital, ie, the knowledge greatest source

of value creation. In addition, the following factors

are in features and challenges inherent to software

development: i)the software is an intangible, which

costs are concentrated in engineering. It is a high

value asset that multiplies without generating new

costs; ii) the software does not suffer physical de-

preciation, possible failures are the result of faults of

project; iii) diversity and volume of knowledge in-

volved, which may be related to processes, products

and skills; and, iv) dynamics of evolution technolo-

gies, techniques and methodologies.

Software production is dependent on knowledge

by those involved, which take various decisions, each

with several options available. In this sense, the expe-

rience constitutes a valuable resource that can be ex-

ploited ((Kavitha and Ahmed, 2011); (Panagiotou and

Mentzas, 2011); (Franca et al., 2012).Another aspect

to be considered in the production of software refers

to the dynamics of knowledge that evolves along with

technology, culture and practices adopted (Iuliana,

2009).

Software Engineering, over the years has sup-

ported the software production with theories, tech-

niques and methods. However, the increased com-

plexity of software projects, scope and smaller deliv-

ery time have conﬁrmed that projects often go beyond

the schedule and estimated costs and therefore do not

meet the quality requirements speciﬁed by the cus-

tomer (Dingsyr, 2002).

Other factors that also slow down productivity

and increase production costs are related to staff

turnover and difﬁculty in identifying, locating and us-

ing knowledge. By integrating new team members,

usually, there is a need to develop skills and com-

petencies related to the processes, technologies and

tools used, as well as knowledge about the domain.

The above factors, in most cases, result in the inabil-

ity to meet demand, resulting in economic loose and

threats to competitiveness. The knowledge capitaliza-

tion shows itself as an effective alternative to address

these issues, it aims to convert knowledge into orga-

nizational assets so that they can be managed and thus

minimize the problems related to: loss of knowledge,

learning curve, repeating mistakes , rework and staff

turnover.

Knowledge Management shows up as an alterna-

tive to improve the efﬁciency in software engineer-

ing, since it make possible to capture, disseminate,

reuse the generated knowledge. So, it is make pos-

sible to obtain better quality product and also in-

crease team productivity (Vasumathy, 2012). Further-

more, (Komi-Sirvio et al., 2002) and (Chongsringam

and Prompoon, 2008) show that knowledge manage-

ment supports process improvement and its products.

Therefore, to achieve the requirements of time, cost

and quality, organizations need to deﬁne ways to man-

age adequately the range of skills involved in Soft-

ware Engineering.

Knowledge Management in Software Engineer-

ing has been addressed by several authors who sug-

gest that Knowledge Management can be used to re-

duce development time, improve decision making,

promote good practices, facilitate communication and

human resource allocation, and so, improve esti-

mates, avoid repeat mistakes, provide cheaper prod-

ucts, among others.

Models, practices, techniques and tools for knowl-

edge Management in Software Engineering are high-

lighted in the literature. In general, practical, tech-

niques and tools are presented as a solution to a spe-

ciﬁc problem, such as knowledge acquisition. How-

ever the models, due its abstraction level, deﬁne what

should be done for Knowledge Management, provide

guidelines for the instantiation of it. In this context,

a gap and a research opportunity to deﬁne a method

that allows to convert Software Engineering knowl-

edge in organizational assets. This conversion from

artifacts, which represent the knowledge materializa-

tion, since they are designed to meet the strategic ob-

jectives and represent investments which, it is hoped,

that add value (SEI, 2010).

The knowledge capitalization includes aspects re-

lated to the location, preservation, value addition and

updating of knowledge, in order to use it in the im-

plementation of new tasks and, thus, increase the

company’s capital. In the context of Software Engi-

neering, the knowledge capitalization facilitates the

access, minimize the loss of knowledge, reduce the

learning curve, avoid repetition mistakes and rework.

So, a capitalization method is presented as a solution

to facilitate access and to reduce the loss of critical

knowledge, which impacts on reducing costs and de-

velopment time, as well as to improve the quality of

software products.

Know-Cap:AMethodforKnowledgeCapitalizationinSoftwareEngineering

4 STATE OF THE ART

The knowledge capitalization is an important step in

the process of organizational knowledge generation.

It aims to reuse the knowledge, previously stored

and modeled, in order to perform new tasks((Simon,

1996); (Morello et al., 2005); (Butdee, 2011)).

According to (Butdee, 2011), capitalization aims

to build a capital information and improve it from

disclosure. It is a process to use, exploit and

reuse knowledge. (Rasovska et al., 2008) describe

the knowledge capitalization as the formalization

of experience in a speciﬁc ﬁeld. (Grundstein and

Rosenthal-Sabroux, 2005) suggest that the identiﬁca-

tion and evaluation of knowledge, which justiﬁes the

capitalization assumes a process of decision making.

To (Busch, 2006), the capitalization of knowledge

is a mechanism to formalize the knowledge of judging

the knowledge produced and used as the company’s

wealth and proﬁt from it, thus helping to increase

the amount of capital. According to (Sarirete and

Chick, 2008) capitalization is the process to identify,

locate, model, store, access, use, reuse, share and up-

date knowledge. In this same sense, (Rasovska et al.,

2008) show that the main purpose of capitalization is

to locate, explain, maintain, access, use, update and

disseminate knowledge in order to value it.

According to (Bolanle et al., 2009) the knowledge

capitalization can be seen as the task of mapping ex-

isting knowledge specifying what, when and where in

order to reuse it.

(Matta et al., 2001) deﬁne four steps for knowl-

edge capitalization , namely: i) extraction and for-

malization of knowledge ii) knowledge sharing; iii)

reuse and appropriation of knowledge, and, iv) devel-

opment of organizational memory.

(Grundstein, 2000) emphasizes that the capitaliza-

tion is not just a technical activity, but an essential

management activity. (Tseng and Huang, 2005) show

that it is necessary to identify the fundamental knowl-

edge for the organization. This identiﬁcation is to de-

ﬁne, locate, characterize and classify the knowledge

to be capitalized. In addition, the authors empha-

size that it is important to capitalize, especially tacit

knowledge.

(Grundstein et al., 2003) present an approach to

solving problems of knowledge capitalization, char-

acterized by four facets (locate, preserve, add value

and update) and their interactions (manage).

The ﬁrst aspect refers to the location of the critical

knowledge, which is knowledge (explicit knowledge)

and know-how (tacit knowledge) necessary for deci-

sion making and for the progress of the key processes

that constitute the core of activities. It is necessary

to identify them, to ﬁnd them, describe them, estimat-

ing their economic value and organize them hierarchi-

cally. (Tseng and Huang, 2005) emphasize that the

choice of knowledge to be capitalized, often, is con-

ditioned by the availability of tools and / or processes,

without really considering the question of the utiliza-

tion of such knowledge, ie, identify the problems that

need knowledge.

(Rasovska et al., 2008) mention that the process of

identiﬁcation and location of knowledge depends on

the objectives and requirements of knowledge man-

agement. In addition, the authors highlight that the

knowledge acquisition is performed from a domain

analysis, technical documents and interviews with ex-

perts.

The second aspect is related to the preservation

of knowledge and know-how, which encompasses

the activities of acquiring, modeling, formalizing and

preserving knowledge. The third aspect concerns the

added value is therefore necessary to increase the

value of knowledge, putting it at the service of devel-

opment and expansion of the company. Ie, knowledge

must be accessible in accordance with rules of conﬁ-

dentiality and security, disclosed, shared and used ef-

fectively to be able to be combined and generate new

knowledge. According to (Rasovska et al., 2008), the

third facet is the capitalization of knowledge, ie, make

knowledge accessible to integrate it and spread it.

The fourth aspect concerns the updating of knowl-

edge and know-how, which includes assessment

activities, updates, standardization, enrichment of

knowledge according to the experiences and new

knowledge creation. (Rasovska et al., 2008) empha-

size that this step is based on feedback and experi-

ence.

The ﬁfth facet, management, is related to the in-

teraction among the facets mentioned above and cov-

ers all management actions in order to respond to

the problem of capitalization of knowledge, namely:

aligning knowledge management with the strategic

directions of the organization, raising awareness peo-

ple; training, encourage and motivate all stakehold-

ers of the organization; waking up the implementa-

tion of favorable conditions for cooperative work and

encourage knowledge sharing; developing indicators

for monitoring and ensuring the coordination of ac-

tions to measure results and determine the relevance

and impact of the actions.

(Renaud et al., 2004) and (Marcandella et al.,

2009) highlight that the main steps for knowledge

capitalization are: locate (identify and characterize),

preserve (model and store), value (use, access, dis-

semination and creation ) and maintain (update and

improve). According to (Marcandella et al., 2009) the

IC3K2013-DoctoralConsortium

knowledge capitalization can be described as a cycle

that involves data collection, data selection, data vali-

dation and knowledge modeling .

(Grundstein, 2000), (Grundstein et al., 2003) and

(Grundstein and Rosenthal-Sabroux, 2005) propose

a framework GAMETH, which provides information

leading to the identiﬁcation of problems, clariﬁcation

of the knowledge requirements, and it also, identiﬁ-

cation, location, speciﬁcation and evaluation based on

the value to determine the crucial knowledge.

The main steps of the GAMETH framework are:

framing the project, identiﬁcation of crucial knowl-

edge and determination of the axes of knowledge

management initiatives. The ﬁrst step is to specify the

context of the project, the domain, the limits of inter-

vention and the processes that will be analyzed, ie,

the processes sensitive. The second step identiﬁes the

activities that may pose risks to sensitive processes.

This identiﬁcation is performed through the follow-

ing steps: modeling of sensitive processes; determi-

nation of the critical activities of sensitive processes,

identiﬁcation of constraints, and outline the potential

crucial knowledge. Finally, in the third step are de-

ﬁned, identiﬁed and characterized the knowledge to

be capitalized. This step consists of the following ac-

tivities: clariﬁcation of the knowledge requirements,

location and characterization of knowledge, assessing

the value of knowledge and determination of critical

knowledge; outline of the project to improve the pro-

cesses of decision making, and determination of the

axes of knowledge management initiatives.

Case studies with the framework GAMETH in

French Institue of Petroleum (IFP), PSA Peugeot Cit-

roen and the French National Center for Scientiﬁc

Research (CNRS) which enabled to show the rele-

vance of the framework to clarify the requirements of

knowledge.

(Matta et al., 2001) describe how to capitalize

the knowledge using the MASK method (Method of

Analysis and Knowledge Structuring). The authors

show that this method can be used in several ﬁelds

such as: security, business processes, mechanical de-

sign and others. With MASK method the knowledge

is structured in systemic analysis ergocognitive, psic-

ocognitive, and historical evolution.

(Sarirete and Chick, 2008) present a model to

solve the problem of knowledge capitalization, tacit

and explicit ones, in the ﬁeld of engineering, within

an online community of practice. The knowledge

capitalization process is proposed to locate the criti-

cal knowledge (identiﬁcation, mapping and classiﬁca-

tion), update it, improve it and preserve it (modeling,

formalizing and archiving), bringing several perspec-

tives of community members in different contexts.

In (Sarirete and Chick, 2008) knowledge rep-

resentation is made through ontologies, in which

knowledge is categorized as experiential, concep-

tual, systemic and routines ones. The experiential

knowledge consists of practical experiences, skills

acquired through discussion, dialogue and common

practices. Conceptual knowledge is explicit knowl-

edge articulated through images, symbols and lan-

guages. The systemic knowledge consists of product

speciﬁcations, manuals and documents. Finally, rou-

tines knowledge is the tacit ones that is customized

and embedded in actions and practices.

The capitalization process model was tested in

two online communities of practice, which share their

documents in a repository for easy access. The study

results indicated that the majority of knowledge was

capitalized as systemic ones. The experiential knowl-

edge, conceptual and routine are not capitalized.

(Rasovska et al., 2008) present an approach for

knowledge capitalization in maintenance. The ap-

proach consists of four steps: detect, protect, update

and capitalize. The detection Phase detection is used

analytical methods and tools of maintenance engi-

neering. In preservation step are used UML (Uniﬁed

Modeling Language) diagrams, particularly the class

diagram for representing knowledge. Case-based rea-

soning is the technique to facilitate the knowledge

reuse. The authors mention that the proposed ap-

proach suggests the implementation of an information

system that includes such steps and automate the pro-

cess of knowledge capitalization.

(Rodriguez-Rocha et al., 2009) describe an ontol-

ogy for the knowledge capitalization in the automo-

tive industry. The ontology is described based on

ISO / TS 16949 and enables knowledge representa-

tion, manipulation and retrieval of documents.

(Butdee, 2010) and (Butdee, 2011) present a

model of knowledge capitalization to design injec-

tion molding. The model is divided into three parts:

knowledge capitalization, knowledge-based system

and products and requirements. The knowledge-

based system is integrated with the capitalization to

explore, reformat and reuse knowledge. It used the

case-based reasoning technique. The representation

of the case is performed by means of global and local

problems. In cases of recovery nearest neighbor tech-

nique is used. The authors emphasize that the most

important part for capitalization is the package of or-

ganizational memory, which consists of a dynamic

memory.

(Castillo-Barrera et al., 2011) use ontologies and

semantic technologies to capitalize the knowledge in

a factory-based software components. The authors

note that it is possible to capitalize the knowledge us-

Know-Cap:AMethodforKnowledgeCapitalizationinSoftwareEngineering

ing ontologies, because they have a more signiﬁcant

meaning. Furthermore, the use of ontologies enables

the search for information about a speciﬁc component

using intelligent techniques, such as production rules.

The paper only presents information on the capital-

ization is performed, only highlights the possibility

of capitalization.

So, Were not found in the literature, to date, stud-

ies about the knowledge capitalization in software en-

gineering. However there are reports on the knowl-

edge capitalization in other areas, as described above.

Not being presented papers that address how to treat

capitalization in knowledge intensive activities like

software engineering.

Furthermore ((Grundstein, 2000), (Grundstein

et al., 2003), (Grundstein and Rosenthal-Sabroux,

2005), (Sarirete and Chick, 2008), (Rasovska et al.,

2008), (Butdee, 2010), and (Butdee, 2011)) describe

models / frameworks for the knowledge capitaliza-

tion. These studies focused on the steps involved in

the cycle of capitalization. However, they not pro-

vide information on how to conduct each one of these

steps, ie, ﬁnd the critical knowledge, how to preserve

knowledge, add value and update it. The level of de-

tail of the models does not identify how each of these

steps must be conducted so that the knowledge to be

capitalized.

The framework proposed by ( (Grundstein, 2000),

(Grundstein et al., 2003), (Grundstein and Rosenthal-

Sabroux, 2005)) is generic, ie it can be applied in

any industry. Case studies were conducted using this

framework in the automotive industry and research.

The model presented by (Sarirete and Chick, 2008)

is facing the engineering domain. The approach of

(Rasovska et al., 2008) is focused on maintaining and

the model proposed by (Butdee, 2010) focuses on

capitalizing on the design of injection molding.

(Matta et al., 2001), (Rodriguez-Rocha et al.,

2009) e (Castillo-Barrera et al., 2011) present works

that describe techniques that can be used in the knowl-

edge capitalization. These studies do not provide in-

formation about the steps of capitalization.

In (Rodriguez-Rocha et al., 2009) and (Castillo-

Barrera et al., 2011) were used ontologies to capital-

ize the knowledge. (Rodriguez-Rocha et al., 2009)

present an ontology for the automotive sector and

(Castillo-Barrera et al., 2011) an ontology for a plant-

based software components. (Matta et al., 2001) de-

scribe how the MASK method can be used to capital-

ize knowledge.

It is possible to notice that the works can be

grouped into two fronts. One that describes mod-

els for capitalization and one which highlights tech-

niques (ontologies, semantic technologies, and case-

based reasoning) that can be employed to capitalize

knowledge.

In general, the studies show that models follow the

same structure as capitalization, which is to identify

critical knowledge, maintain, capitalize and update.

These models are generic, not speciﬁc to a domain,

and are not prescriptive, ie, do not provide informa-

tion on how to perform each of these steps, thus set-

ting a gap and a research opportunity.

In relation to software engineering, in the litera-

ture, aspects related to Knowledge Management are

discussed. However, capitalization is still a topic to

be explored. In this regard, it is noteworthy that the

gap is the deﬁnition of a capitalization method spe-

ciﬁc to the area of Software Engineering, which al-

lows to identify, select and convert knowledge into

organizational assets.

5 METHODOLOGY

The research can be characterized as applied, which

aims to generate knowledge for practical application.

It is planned to conduct this research in three

phases: Exploratory Study, Deﬁnition and Reﬁne-

ment Method.

In Exploratory Study phase a literature review was

performed. Whit that a consistent theoretical basis

for continuing study and visualize the state of the art.

Concepts related to software engineering, CMMI ma-

turity model, capitalization of knowledge, knowledge

management and knowledge management in software

engineering were also studied.

In the second phase, the Know-Cap will be de-

ﬁned. It will be performed based on the gaps identi-

ﬁed on the previous phase. So, the main activities for

the method and also to adequate representation for the

knowledge will be deﬁned.

After the method deﬁnition, will occur the Reﬁne-

ment phase. Initially is expected to undertake the fol-

lowing activities:

• Feasibility Study: the aim is to acquire knowledge

about the application of the method, allowing the

generation of new hypotheses. This study will be

conducted in the academic and industrial commu-

nity.

• Case Study: the objective it to determine the prac-

tical feasibility of the method in order to improve

the understanding of researchers and characterize

the application.

IC3K2013-DoctoralConsortium

6 EXPECTED OUTCOME

The main result is a method for knowledge capitaliza-

tion that enables to convert knowledge into organiza-

tional asset. It can also highlighted the following re-

sults: the knowledge categorization in software engi-

neering, which facilitates access and retrieval, to iden-

tify strategies that enable to select the critical knowl-

edge, and the deﬁnition of guidelines that guide the

implementation of activities, as well as the deﬁnition

of templates for each of the artifacts.

A capitalization method provides guidelines re-

garding the identiﬁcation and selection of the critical

knowledge, which enables to obtain improvements on

the software development process and also on prod-

uct quality. The improvements are related to integra-

tion of new member since they will have access to the

organizational knowledge. So, using Know-Cap, the

idea is to avoid knowledge loss, reduce learning curve

and improve knowledge retention.

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IC3K2013-DoctoralConsortium