Automated Analysis of Requirement Specifications

ABSTRACT

It is generally accepted that poorly written requirements can result in software with the wrong functionality. The Goddard Space Flight Center's (GSFC) Software Assurance Technology Center (SATC) has developed an early life cycle tool for assessing requirements that are specified in natural language. The tool searches the document for terms the SATC has identified as quality indicators, e.g. weak phrases. The reports produced by the tool are used to identify specification statements and structural areas of the requirements specification document that need to be improved. The metrics are used by project managers to recognize and preclude potential areas of risk.

INTRODUCTION

The SATC is part of the Office of Mission Assurance of the GSFC. The SATC's mission is to assist National Aeronautics and Space Administration (NASA) projects to improve the quality of software that they acquire or develop. The SATC's efforts are currently focused on the development and use of metric methodologies and tools that identify and assess risks associated with software performance and scheduled delivery. It is generally accepted that the earlier in the life cycle that potential risks are identified the easier it is to eliminate or manage the risk inducing conditions [1].

Despite the significant advantages attributed to the use of formal specification languages, their use has not become common practice. Because requirements that the acquirer expects the developer to contractually satisfy must be understood by both parties, specifications are most often written in natural language. The use of natural language to prescribe complex, dynamic systems has at least three severe problems: ambiguity, inaccuracy and inconsistency [11]. Many words and phrases have dual meanings which can be altered by the context in which they are used. For example, Webster's New World Dictionary identifies three variations in meaning for the word "align", seventeen for "measure", and four for the word "model". Weak sentence structure can also produce ambiguous statements. "Twenty seconds prior to engine shutdown anomalies shall be ignored." could result in at least three different implementations. Using words such as "large", "rapid", and "many" produces inaccurate requirement specifications. Even though the words "error", "fault", and "failure" have been precisely defined by the Institute of Electrical and Electronics Engineers (IEEE) [5] they are frequently used incorrectly. Defining a large, multi-dimensional capability within the limitations imposed by the two dimensional structure of a document can obscure the relationships between individual groups of requirements.

The importance of correctly documenting requirements has caused the software industry to produce a significant number of aids [3] to the creation and management of the requirements specification documents and individual specifications statements. Very few of these aids assist in evaluating the quality of the requirements document or the individual specification statements. This situation has motivated the SATC to develop a tool to provide metrics that NASA project managers can use to assess the quality of their requirements specification documents and to identify risks that poorly specified requirements will introduce into their project. It must be emphasized that the tool does not attempt to assess the correctness of the requirements specified. It assesses the structure of the requirements document and individual specification statements and the vocabulary used to state the requirements.

BACKGROUND

The SATC study was initiated by compiling a list of quality attributes that requirements specifications are expected to exhibit [6] [11]. The next step was to list of those aspects of a requirements specification that can be objectively and quantitatively measured. The two lists were analyzed to identify relationships between what can be measured and the desired quality attributes. This analysis resulted in the identification of categories and individual items that are primitive indicators of the specification's quality and can be detected and counted by using the document's text file.

Concurrent with development and analysis of the attribute and indicator lists, forty-six requirement specifications were acquired from a broad cross section of NASA projects. These documents were converted into ASCII text files. These files were used to develop a database containing the words and phrases used in the set of document and the number of times that they occurred. This database of basic words was used to refine the list of primitive indicators.

Using the refined list of primitive indicators, an initial version of the Automated Requirements Measurement (ARM) software was developed for scanning the specification files. ARM was used to subject each specification file to a full text scan for occurrences of each of the quality primitives. The occurrence of primitives within each file were totaled and reported individually and by category. Correlation between all totals were examined for significant relationships. Files that exhibited anomalous data and off-norm counts were examined to determine the source of these aberrations. A tentative assessments of each requirements document's quality was made based on this analysis and examinations. The source requirements documents are currently being independently reviewed to provide a basis of comparison with the conclusions arrived at using the ARM's reports.

While the source documents are being independently reviewed, the prototype ARM software is being used to aid selected NASA projects to strengthen their requirement specifications. The results of the engineering assessments and feedback from the selected NASA projects will be used to improve ARM's assessment processes and its user interface.

SPECIFICATION QUALITY ATTRIBUTES

The desirable characteristics for requirements specifications[2] [6] are:

• Complete
• Consistent
• Correct
• Modifiable
• Ranked
• Traceable
• Unambiguous
• Verifiable

As a practical matter, it is generally accepted that requirements specifications should also be Valid and Testable. These characteristics are not independent. For example, McCall's quality model [7] identifies tractability, completeness, and consistency as being factors which contribute to correctness. Also, the ISO 9126 software quality model [7] gives stability, modifiability (changeability), and testability as factors contributing to maintainability. A specification, obviously, cannot be correct if it is incomplete or inconsistent.

Most, if not all, of these quality attributes are subjective. A conclusive assessment of a requirements specification's appropriateness requires review and analysis by technical and operational experts in the domain addressed by the requirements. Several of these quality attributes, however, can be linked to primitive indicators that provide some evidence that the desired attributes are present or absent. These primitives are alluded to in the attribute definitions below.

Complete
A complete requirements specification must precisely define all the real world situations that will be encountered and the capability's responses to them [11]. It must not include situations that will not be encountered or unnecessary capability features.

Consistent
A consistent specification is one where there is no conflict between individual requirement statements that define the behavior of essential capabilities; and specified behavioral properties and constraints do not have an adverse impact on that behavior [11]. Stated another way, capability functions and performance level must be compatible and the required quality features (reliability, safety, security, etc.) must not negate the capability's utility. For example, the only aircraft that is totally safe is one that cannot be started, contains no fuel or other liquids, and is securely tied down.

Correct
For a requirements specification to be correct it must accurately and precisely identify the individual conditions and limitations of all situations that the desired capability will encounter and it must also define the capability's proper response to those situations [11]. In other words, the specification must define the desired capability's real world operational environment, its interface to that environment and its interaction with that environment. It is the real world aspect of requirements that is the major source of difficulty in achieving specification correctness. The real world environment is not well known for new applications and for mature applications the real world keeps changing. The COBOL problem with the transition from the year 1999 to the year 2000 is an example of the real world moving beyond an application's specified requirements.

Modifiable
In order for requirements specifications be modifiable, related concerns must be grouped together and unrelated concerns must be separated [6] [10]. This characteristic is exhibited by a logical structuring of the requirements document. Structuring the document to be modifiable may conflict with the ranking of specifications according to stability and/or importance.

Ranked
Ranking specification statements according to stability and/or importance is established in the requirements document's organization and structure [6]. The larger and more complex the problem addressed by the requirements specification, the more difficult the task is to design a document that aids rather than inhibits understanding.

Testable
In order for a specification to be testable it must be stated in such as manner that pass/fail or quantitative assessment criteria can be derived from the specification itself and/or referenced information [10].

Traceable
Each statement of requirement must be uniquely identified to achieve traceability [10]. Uniqueness is facilitated by the use of a consistent and logical scheme for assigning identification to each specification statement within the requirements document. If each specification is expressed as a fundamental and uncomplicated statement, the structure and uniqueness of the requirements document's identifications can be objectively assess by relatively simple algorithms. The extent that a specification is fundamental is subjective based on the assessor's knowledge of the application domain, whereas certain phrases and sentence structures that indicate a complicated statement can be objectively identified.

Unambiguous
A statement that specifies a requirement is unambiguous if it can only be interpreted one way [10]. This perhaps, is the most difficult attribute to achieve using natural language. The use of weak phrases or poor sentence structure will open the specification statement to misunderstandings.

Valid
To validate a requirements specification all the project participants, managers, engineers and customer representatives, must be able to understand, analyze and accept or approve it [11]. This is the primary reason that most specifications are expressed in natural language.

Verifiable
In order to be verifiable requirement specifications at one level of abstraction must be consistent with those at another level of abstraction [11].

SPECIFICATION QUALITY INDICATORS

Although most of the quality attributes of documented requirements are subjective, there are aspects of the documentation which can be measured and are indicators of quality attributes. Size, which is a primitive used in many quality metrics, can be directly measured. The size of an individual specification statement can be measured by the number of words it contains. The size of a requirements document can be easily measured by the number of pages, the number of paragraphs, lines of text, or the number of individual specification statements it contains. The number of unique subjects addressed by specification statements within the requirements document can also be counted with relative ease. This count is an indication of the scope of the requirements encompassed by the document. The breadth and hierarchical depth encompassed by the document's specification statements can be measured using the document's internal identification scheme. These measures provide clues to the document's organization and depth of detail. The number of specification statements at each level of the document's structure can also be counted. These counts provide an indication as to how the specification statements are organized and the level of detail to which requirements are specified. It is also possible to count the occurrence of specific words and phrases that signal that specification statements are weak or strong.

Categories
Nine categories of quality indicators for requirement documents and specification statements were established based on a representative set of NASA requirements documents selected from the SATC's library. Individual indicators were identified by finding frequently used words, phrases, and structures of the selected documents that were related to quality attributes and could be easily identified and counted by a computer program. These individual indicators were grouped according to their indicative characteristics. The resulting categories fall into two classes. Those related to the examination of individual specification statements and those related to the total requirements document. The categories related to individual specification statements are:

• Imperatives
• Continuance
• Directives
• Options
• Weak Phases

The categories of indicators related to the entire requirements document are:

• Size
• Specification Depth
• Readability
• Text Structure

Imperatives
Imperatives are those words and phrases that command that something must be provided. The ARM report lists the total number of times each imperatives was detected in the sequence that they are discussed below. This list presents imperatives in descending order of their strength as a forceful statement of a requirement. The NASA requirements documents that were judged to be the most explicit had the majority of their imperative counts associated with the upper list items.

• Shall is usually used to dictate the provision of a functional capability.
• Must or must not is most often used to establish performance requirements or constraints.
• Is required to is often used as an imperative in specifications statements written in the passive voice.
• Are applicable is normally used to include, by reference, standards or other documentation as an addition to the requirements being specified.
• Responsible for is frequently used as an imperative in requirements documents that are written for systems whose architectures are predefined. As an example, "The XYS function of the ABC subsystem is responsible for responding to PDQ inputs."
• Will is generally used to cite things that the operational or development environment are to provide to the capability being specified. For example, "The building's electrical system will power the XYZ system". In a few instances "shall" and "will" were used interchangeably within a document that contained both requirements specifications and descriptions of the operational environment. In those documents, the boundaries of the system being specified were not always sharply defined.
• Should is not frequently used as an imperative in requirement specification statements. However, when is used, the specifications statement is always found to be very weak. For example, "Within reason, data files should have the same time span to facilitate ease of use and data comparison."

Continuances
Continuances are phrases such as those listed below that follow an imperative and introduce the specification of requirements at a lower level. The extent that continuances were used was found to be an indication that requirements were organized and structured. These characteristics contribute to the tractability and maintenance of the subject requirement specification. However, in some instances, extensive use of continuances was found to indicate the presence of very complex and detailed requirements specification statements. The continuances that the ARM tool looks for are listed below in the order most frequently found in NASA requirements documents.

• below:
• as follows:
• following:
• listed:
• in particular:
• support:

Directives
Directives is the category of words and phrases that point to illustrative information within the requirements document. The data and information pointed to by directives strengthens the document's specification statements and makes them more understandable. A high ratio of the total count for the Directives category to the documents total lines of text appears to be an indicator of how precisely requirements are specified. The directives that the ARM tool counts are listed below in the order that they are most often encountered in NASA requirements specifications.

• figure
• table
• for example
• note:

Options
Options is the category of words that give the developer latitude in satisfying the specification statements that contain them. This category of words loosen the specification, reduces the acquirer's control over the final product, and establishes a basis for possible cost and schedule risks. The words that the ARM tool identifies as options are listed in the order that they are most frequently used in NASA requirements documents.

• can
• may
• optionally

Weak Phrases
Weak Phrases is the category of clauses that are apt to cause uncertainty and leave room for multiple interpretations. Use of phrases such as "adequate" and "as appropriate" indicate that what is required is either defined elsewhere or, worse, that the requirement is open to subjective interpretation. Phrases such as "but not limited to" and "as a minimum" provide a basis for expanding a requirement or adding future requirements. The total number of weak phrases found in a document is an indication of the extent that the specification is ambiguous and incomplete. The weak phrases reported by the ARM tool are:

• adequate
• as a minimum
• as applicable
• easy
• as appropriate
• be able to
• be capable
• but not limited to
• capability of
• capability to
• effective
• if practical
• normal
• provide for
• timely

Size
Size is the category used by the ARM tool to report three indicators of the size of the requirements specification document. They are the total number of:

• lines of text
• imperatives
• subjects of specification statements
• paragraphs

The number of lines of text in a specification document is accumulated as each string of text is read and processed by the ARM program. The number of subjects used in the specification document is a count of unique combinations and permutations of words immediately preceding imperatives in the source file. This count appears to be an indication of the scope of the document. The ratio of imperatives to subjects provides an indication of the level of detail being specified. The ratio of lines of text to imperatives provides an indication of how concise the document is in specifying the requirements.

Text Structure
Text Structure is a category is used by the ARM tool to report the number of statement identifiers found at each hierarchical level of the requirements document. These counts provide an indication of the document's organization, consistency, and level of detail. The most detailed NASA documents were found to have statements with a hierarchical structure extending to nine levels of depth. High level requirements documents rarely had numbered statements below a structural depth of four. The text structure of documents judged to be well organized and having a consistent level of detail were found to have a pyramidal shape (few numbered statements at level 1 and each lower level having more numbered statements than the level above it). Documents that exhibited an hour-glass shaped text structure (many numbered statements at high levels, few at mid levels and many at lower levels) were usually those that contain a large amount of introductory and administrative information. Diamond shaped documents (a pyramid followed by decreasing statement counts at levels below the pyramid) indicated that subjects introduced at the higher levels were addressed at different levels of detail.

Specification Depth
Specification Depth is a category used by the ARM tool to report the number of imperatives found at each of the documents levels of text structure. These numbers also include the count of lower level list items that are introduced at a higher level by an imperative and followed by a continuance. This data is significant because it reflects the structure of the requirements statements as opposed to that of the document's text. Differences between the Text Structure counts and the Specification Depth were found to be an indication of the amount and location of text describing the environment that was included in the requirements document. The ratio of the total for specification depth category to document's total lines of text appears to be an indication of how concise the document is in specifying requirements.

Readability Statistics
Readability Statistics are a category of indicators that measure how easily an adult can read and understand the requirements document. Four readability statistics produced by Microsoft Word are currently calculated and compared:

• Flesch Reading Ease index is based on the average number of syllables per word and the average number of words per sentence. Scores range from 0 to 100 with standard writing averaging 60 - 70. The higher the score, the greater the number of people who can readily understand the document.
• Flesch-Kincaid Grade Level index is also based on the average number of syllables per word and the average number of words per sentence. The score in this case indicates a grade-school level. A score of 8.0 for example, means that an eighth grader would understand the document. Standard writing averages seventh to eighth grade.
• Coleman-Liau Grade Level index uses word length in characters and sentence length in words to determine grade level.
• Bormuth Grade Level index also uses word length in characters and sentence length in words to determine a grade level.

Since most documents at NASA contain scientific terms which tend to contain words of considerable length, the readability scores are skewed. As shown in the table below, using the data from forty-six requirements documents, the grade levels indicated by the Flesch-Kincaid, Coleman-Liau and Bormuth have a high variance, and the mean for Coleman-Liau grade level is 27.6 with a maximum of 55.80. Alternative readability packages that allow for adjustment of word length are being investigated.

Relationships between requirements specifications' quality attributes and categories of indicators measured by the ARM tool are shown below in Figure 1.

Figure 1.

RISK

As the first tangible representation of the needed capability, the requirements specification establishes the basis for all of the project's engineering, management and assurance functions. If the quality of the requirements specification is poor, it can give rise to risks associated with the project's products and its resources. Inadequate requirements can directly impact the quality aspects of the product that is to be produce. Deficient requirements can also induce delays and rework and thereby directly impact the project's costs and delivery schedules

Acceptance Risk
A deficiency in any of the requirements specification's quality attributes can introduce a risk that the product will not be acceptable to the user in its intended operational environment.

Availability Risk
If the requirements specification is incomplete, incorrect, not modifiable, not properly ranked, or not testable there will be a corresponding risk that capabilities will not be provided when need.

Performance Risk
A risk that the delivered capability will not perform adequately will arise if the requirements specification is difficult to understand or inadequately specifies the functions that are to be provided.

Reliability Risk
A deficiency in any of the requirements specification's quality attributes can introduce a risk that the product will not achieve the level of reliability need to successfully perform its mission in the operational environment

Reproducibility Risk
If the requirements specification is poorly written and functions are inadequately prescribed there will be a risk that the product or components of the product cannot be replicated when replacement is necessary.

Supportability Risk
A deficiency in any of the requirements specification's quality attributes can introduce a risk that the product cannot be adequately supported in the operational environment.

Utility Risk
A risk that the delivered capability will not provide the user with the full range of necessary functionality will arise if the requirements specification is difficult to understand or the functions that are to be provided are inadequately specified.

Cost Risk
Any deficiency in the requirements specification, such as incompleteness, that causes the development effort to be under estimated or necessitates rework, such as ambiguity, will introduce a risk that costs will exceed the available funding.

Schedule Risk
A deficiency in any of the requirements specification's quality attributes can introduce a risk that the project's schedule is inadequate and the product will not be delivered on time.

Quality-Risk Relationships
Figure 2 shows the areas of project risk that are directly impacted by the quality attributes of the requirements specification.

Figure 2.

SPECIFICATION STANDARDS

Although many government and several professional organizations have published documentation standards that include standards for specifying requirements, none are universally accepted or extensively enforced. NASA has very explicit software documentation standards and style guides, but it allows wide latitude in establishing project standards. In many instances, to minimize effort and reduce costs, projects choose to accept the documentation standards and procedures of the contractor selected to provide the needed capability. Smaller projects, of which there are many in-house in addition to contractual acquisitions, are also frequently combine requirement and design documents to conserve project resources. Even the standards that are imposed seldom go beyond providing an outline and general description of the information to be provided. In many cases no style requirements are established. As a consequence, requirements documents from various sources bear little resemblance to one another.

The content outline of one of the IEEE's eight specification templates [6] and NASA's standard data item description (DID) for requirement specifications documents [8] are shown below and provide an example of the variance in scope that exists between standards.

IEEE 830 93

Software Requirement Specification

1. Introduction

2. Overall description

3. Specific requirements

Appendixes
Index

NASA-DID-P200

Requirements

1.0 Introduction
2.0 Related documentation
3.0 Requirements approach and trade offs
4.0 External interface requirements
5.0 Requirements specification

6.0 Traceability to parent's design
7.0 Partitioning for phased delivery
8.0 Abbreviations and acronyms
9.0 Glossary
10.0 Notes
11.0 Appendices

Several problems related to the structure and organization of the source documents were frequently encountered when attempting to automate the scanning of specification files. The most troubling problem was the inconsistency in paragraph and specification identification across documents and within documents. The variations in identification schemes most frequently encountered are shown below in the order of their prevalence.

• Hierarchical Numbers - 1.2.3., 1.2.3.4.., .....1.2.3.4.5.6.7.8., etc.
• Lettered Hierarchical Numbers P1.2.3., Q1.2.3.4.., .....S1.2.3.4.5.6.7.8, etc.
• Integer Numbers - 1., 2.,3.,...10.; 1, 2, 3, 20, 21; 30; [1], [2], [3];[20]
• Letters A., B., C.; a., b., c.; a), b), c); (a), (b), (c)

Because of these numbering inconsistencies the current version of the Automated Requirement Measurement (ARM) software is implemented using the following scheme as the basis for recognizing paragraph and specification identifications.

Each requirement specification statement is assumed to individually distinguished by one of the following markings:

1. A simple number (i.e. a number without decimal. For example: 1, 23, 104, etc.)
2. A hierarchical number (i.e. a number with decimals to indicate levels of structure. For example: 1.1.1, 23.4.5.6, etc.)
3. A lettered hierarchical number (i.e. a hierarchical number immediately preceded by a letter. followed by a period. For example: L1.1.1, B23.4.5.6, etc.)
4. An integer number (i.e. a simple number. For example: 1., 23., 104., etc.)
5. A letter designation (i.e. a single capital/lower-case letter followed by a period. For example: A., P., b., x. etc.)

Another problem encountered when scanning requirement specification files is distinguishing statements that prescribe required system capabilities from those that describe the operational environment. This problem has both structural and terminology aspects. In general three structural separations of descriptive and prescriptive information are usually used. The NASA documentation standards call for information to be presented in two distinct documents. The targeted operational environment is to be described within the NASA Concept Document, NASA-DID-P100 [8] while the standard shown above, NASA-DID-P200, is to contain prescriptive specifications. Other standards [2] [6] allocate descriptive and prescriptive information to separate parts of the same document. In several NASA contractor provided requirements documents the two categories of information were interlaced within the same sections of the document.

In some instances the ability to distinguish between statements prescribing requirements and those describing environmental features was further complicated by authors using the imperatives "shall", will", and "should" interchangeably.

RESULTS

The graphs presented in this section are based on data collected by the ARM processor. The assessments accompanying the graphical presentations are based on an examination of the source documents in light of the data used to create the graphs.

Document Size And Imperatives
The relationship between document size, measured by total number of imperatives and total lines of text found in each specification document is depicted by Figure 3., below.

Figure 3.

The ratio of lines of text to imperatives for each specification document is shown in Figure 4. Most documents have ten lines of text, or less, for each imperative. When inspected, the documents with ratios that exceed one-to-one, appeared to have been created using a requirements analysis methodology or tool. The low ratios resulted of the fact that the documents exclusively addressed software requirements and many single statement contains multiple imperatives connected by "and" or "or". Those specification documents with ratios above ten lines of text per imperative appear to have been developed based on an ad-hoc documentation standards with scopes that includes the description of the operational environment as well a the prescription of system requirements

Figure 4.

The document with the highest ratio of text to imperatives also included descriptions of the project and requirements for the development environment. This extreme data point was removed in Figure 4a. to improve the visibility of the remaining data points.

Figure 4a.

Document Size And Structure
The relationship between document size and depth of the document's text structure, based on paragraph numbering and identification of statements, is shown by Figure 5. In general, the smaller documents have a greater percent of their statements numbered. These documents appear to have been developed using a Computer Aided Software Engineering tool. These documents are very hierarchical in structure. The highest level requirements have been repetitively decomposed into specifications of increasing detail and each statement at every level is numbered.

Figure 6. shows the ratio of numbered statements to the number of imperatives within a specification document. Most NASA documents containing less than 100 imperatives have a high ratio. It appears that these requirements specifications were using a documentation format that was too detailed for the scope of the requirements being specified. The majority of the sections in these documents addressed administrative and general information rather than requirements specifications. In general, documents with more than 100 imperatives seem to have a ratio of numbered statements to imperatives close to one. This implies that these document's specification statements have a high degree of traceability.

Figure 5.

Figure 6.

Imperatives And Subjects
The relationship between the number of imperatives and the unique number of subjects of imperative is shown by Figure 7.. Closer examination of these documents found that the real ratio between subjects and imperatives is actually lower than shown in Figure 8. In many instances the same subject was stated in different terms, apparently to introduce variety and hold the readers interest. The ARM software is not capable of recognizing different phrases as the same subject and counts each distinct combination of words immediately preceding the imperative as a unique subject. The larger documents were found to be much greater in scope and to addressed subjects at a higher level of capability. In these higher level specifications, multiple statements are used to define and bound each major functional capability

Figure 7.

Figure 8. shows the ratio of imperatives to subjects versus lines of text. Within a limited amount of variation, it appears that even in those documents containing many imperatives per subject, each imperative is supported with a nominal number of text lines

Figure 8.

Weak Phrases
Figure 9. shows the number of weak phrases versus the number of imperatives found in NASA requirements documents. Figure 10. Presents the ratio of weak phrases to imperatives versus the number of imperatives contained in the document. In most of these documents it appears that one to ten percent of the individual specification statements contain weak phrases. For some of the smaller documents, those same documents that were well structured and identified due to the use of CASE tools, weak phrases were found in thirty to sixty percent of their individual specification statements.

Figure 9.

Figure 10.

Conclusions and General Observations
Three initial general conclusions have arisen from the subject study, First, it is possible to gain insights as to the quality of a requirements specification through the use of data gathered by automated processing of the specification file. Second, the effectiveness of expressing requirements specifications with natural language can be greatly improved through relatively simple and readily available methods. Lastly, specifications developed using a proven methodology with the aid of a requirements definition tool are better structured, more consistently numbered, and contain crisper specification statements than those developed solely based on a documentation standard. However, use of the tool is not a substitute for sound engineering analysis.

Management Recommendations
Based on the current results of the SATC study it is recommended that project managers ensure that requirements specification and style standards are established at the outset of the project and that all project participants are trained in the use of those standards. It is also recommended that the technical nature and intended use of the requirements document be emphasized to encourage a straightforward writing style and simple sentence structures to specify each requirement. Technical documents are not required to be interesting, however, it is necessary for them to effectively communicate with the reader..

Technical Recommendations
Requirements analysis an development of individual specifications should occur prior to writing the requirements document, not as a by-product of the documentation activity. Requirement specifications should be developed using a methodology that is appropriate to the nature of the project and its products. CASE tool should be used if they support the project's development methodology and the technology being addressed by the project.

Specification writers should be taught how to write simple direct statements. If conditional clauses are needed, they should be placed at the front of the sentence. Subjects, imperative/verb combinations, and objects of the verb should occur in that order. This will prevent interesting, but confusing statements, such as: "The Romans, the Greeks shall defeat if better prepared they be."

Future Work
Three types of enhancements are planned for the ARM software. The enhancement of immediate priority is to improve the ARM tool's user interface and to provide the flexibility to tailor its reports to the user's areas of interest. This will facilitate enlisting additional projects to participate in the SATC study, add their requirements documents to the SATC database and provide user feedback.

The second ARM tool enhancement activity will take place in parallel with the improvement of its user interface and report generator. The results of the engineering review of the requirements specifications in the SATC database will be used to refine ARM's search and counting schemes. This will improve the validity of data produced by the ARM tool and heighten user confidence in the conclusions that can be inferred from its reports

Lastly, once the ARM's search and counting schemes have been enhanced, words and phrases will be identified that can be used as indicators that the following types of requirements have been addressed within the requirements document.

• Acceptance Testing
• Data Handling
• Design Standards
• Integrity
• Maintainability
• Reliability
• Reusability
• Timing and Sizing

REFERENCES

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2. DOD MIL-STD-490A, Specification Practices, June 4, 1985.
3. Ganska, Ralph, Grotzky, John, Rubinstein, Jack, Van Buren, Jim, Requirements Engineering and Design Technology Report, Software Technology Support Center, Hill AFB, October, 1995.
4. Gause, Donald C., and Weinberg, Gerald M., Exploring Requirements Quality Before Design, Dorset House Publishing, NY, NY, 1989
5. IEEE Std 729-1983, Standard Glossary of Software Engineering Terminology, Feburary 18, 1983.
6. IEEE Std 830-1993, Recommended Practice for Software Requirements Specifications, December 2, 1993.
7. Kitchenham, Barbara, Pfleeger, Shari Lawrence, Software Quality: The Elusive Target, IEEE Software, Vol. 13, No. 1, January 1996, pp. 12-21.`
8. NASA-STD-2100-91, NASA Software Documentation Standard, NASA Headquarters Software Engineering Program, July 29, 1991.
9. Porter, Adam A., Votta, Lawrence G., Jr., and Basili, Victor R., Comparing Detection Methods for Software Requirements Inspections: A Replicated Experiment, IEEE Transactions on Software Engineering, Vol. 21, No. 6, June 1995, pp. 563-574.
10. Sommerville, Ian, Software Engineering, Fourth Edition, Addison-Wesley Publishing Company, Wokingham, England, 1992.
11. Stokes, David Alan, Requirements Analysis, Computer Weekly Software Engineer's Reference Book, 1991, pp. 16/3-16/21.

Automated Analysis of Requirement Specifications was Presented at the International Conference on Software Engineergin (ISCE '97), Boston, MA, May 1997.