Role of Software Readability on

1
Role of Software Readability on Software
Development Cost
21st International Forum on COCOMO and Software
Cost ModelingNovember 9, 2006
Ricardo Valerdi, Ph.D. Massachusetts Institute of
Technology Lean Aerospace Initiative 77 Vassar
Street, Bldg 41, Rm 205 Cambridge, MA
02139 rvalerdi_at_mit.edu
Emilio Collar, Jr., Ph.D. Western Connecticut
State University Ancell School of Business 181
White Street Danbury, CT 06811 collare_at_wcsu.edu
Nov 9, 2006
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Presentation Outline

• The High Cost of Software Maintenance
• RUSE cost driver in COCOMO II
• Linking RUSE to readability
• A Cognitive Approach to Text Readability
• Concepts in Software Readability
• Programming Code Textbase Readability Model
  (PCTRM)
• Summary of Key Interpretations
• Implications for Software Cost Estimation

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The High Cost of Software Maintenance

• Typically, 70 of the life cycle cost of software
  is in the maintenance phase (Agresti 1982)
• The high cost of software maintenance is linked
  to the difficulty of reading and understanding
  programming code, particularly code written by
  someone else
• Code reading has been estimated to account for
  more than 50 of the effort expended in software
  maintenance (von Mayrhauser and Vans 1995)

• ? Agresti, W. W. (1982). "Managing program
  maintenance." Journal of Systems Management
  33(2) 34-37.
• von Mayrhauser, A. and A. M. Vans (1995).
  Program Understanding Models and Experiments.
  Advances in Computers.
• M.C. Yovits and M. Zelkowitz (Eds.) San
  Diego, CA, Academic Press. 40 2-36.

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RUSE Cost Driver in COCOMO II

• This phenomenon is captured in COCOMO II costs
  drivers (Boehm, Abts, et al 2000)
• Developing programming code that is more easily
  read by other programmers would reduce the cost
  of maintaining that code (Basili 1997)

Required Reusability (RUSE) This cost driver
accounts for the additional effort needed to
construct components intended for reuse on the
current or future projects. This effort is
consumed with creating more generic design of
software, more elaborate documentation, and more
extensive testing to ensure components are ready
for use in other applications.
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? Boehm, B., C. Abts, et al. (2000). Software
Cost Estimation with COCOMO II. New York,
Prentice Hall. ? Basili, V. R. (1997). "Evolving
and packaging reading technologies." Journal of
Systems and Software, 38 3-12.
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Linking RUSE to Code Readability
Quantifiable
Quantifiable
influences
is affected by
Code Readability
Code Comprehension
Reusability
Key question What affects code comprehension?
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A Cognitive Approach to Text Readability

• Reading and educational measurement
• Text comprehension, vocabulary difficulty
• Linguistics/discourse processing
• Text-reader interaction
• Psychology/natural language
• Cognitive Readability theory (Kintsch and Vipond
  1979)
• Text comprehension proceeds cognitively across
  three textual levels
• Verbatim representation
• The text as written code (orthography)
• Textbase representation
• The text as decontextualized organization of
  literal meaning (an ordered set of propositions)
• Situation model representation
• The text understood as embedded in a situation or
  context

Current focus

• Kintsch, W. and D. Vipond (1979). Reading
  comprehension and readability in educational
  practice and psychological
• theory. Perspectives on memory research. I.
  G. Nillson. Hillsdale, NJ, Erlbaum 329-365.

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Concepts in Software Readability

• Programming languages are like natural languages
• They have a grammatical structure
• They have a linguistic structure
• Give rise to propositions containing
• predicates (relational terms in a string of
  words)
• arguments (associated entities)
• But they are value-neutral
• Mathematical, logical, and intentional aspects
  dominate
• Social and moral aspects are secondary due to
  limitations of the domain (i.e.,
  computer-programmer interaction)
• Text must be evaluated in terms of propositions
  (Kintsch and Vipond 1979) rather than sentences
  (Chomsky 1956)

Key concept proposition as the unit of analysis

• Backus, J. (1960). The syntax and semantics of
  the proposal international algebraic language of
  the Zurich ACM-GAMM
• conference. Zurich ACM-GAMM conference,
  Paris, UNESCO.
• ? Naur, P. (1960). "Report on the algorithmic
  language ALGOL 60." Communications of the ACM
  3(5) 299-314.
• Chomsky, N. (1956). "Three models for the
  description of language." IRE Transactions on
  Information Theory IT-2(3) 113-124.

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Code Readability Example
Example 2a
z ((3x2) (4x) 5) ((2y2) (7y)
11) / ((3x2) (4x) 5)
vs.
Example 2b
a ((3x2) (4x) 5) b ((2y2) (7y)
11) z (a b) / a
Although both examples are comprehensible,
example 2b is comprehensible with greater ease
(i.e., more readable) then example 2a. (Collar
2005, p. 120)

• Collar, E. (2005). An Investigation of
  Programming Code Readability Based on a Cognitive
  Readability Model - Volume I
• Manuscript. Leeds School of Business.
  Boulder, CO, University of Colorado at Boulder
  403.

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Components of the PCTRM

• Propositional Density (PD)
• Greater PD requires greater processing effort on
  the part of the reader this effort makes the
  code more difficult to read.
• Number of New Arguments (NA)
• Greater numbers of NA require the reader to
  manage more concepts in memory this effort makes
  the code more difficult to read.
• Number of Repeated Arguments (RA)
• Greater numbers of RA within and between logical
  lines of code render the program more coherent
  and, therefore, easier to read.
• Number of Branching Reinstatements (RIB)
• The reader performs a RIB whenever integration
  into representational memory of a concept in a
  current proposition requires reference to a
  concept in a proposition found elsewhere in the
  code greater numbers of RIB increase cognitive
  load, making the code more difficult to read.

Programming Code Textbase Readability Model
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Other PCTRM Constructs

• A readers level of skill in effectively using
  cognitive reading processes while reading

• A readers knowledge, both conceptual and
  experiential, about programming and programming
  languages

• Textbase readability arises from the effects of
  specific propositional features of the
  programming code interacting with the cognitive
  reading processes of the reader.

• Textbase comprehension arises from the effects of
  textbase readability interacting with the
  cognitive reading processes of the reader.

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Programming Code Textbase Readability Model
(PCTRM)
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Summary of Key Interpretations

• As Non-Visual Basic-Specific Programming Language
  Experience (ESF1) increases, perceived
  readability (PRSF4) increases
• As Visual Basic Programming Language Experience
  (ESF2) increases, perceived readability (PRSF4)
  increases.
• As Visual Basic Training (ESF3) increases,
  perceived readability (PRSF4) increases (i.e.,
  code becomes easier to read).

• As perceived readability increases (PRSF4), the
  time spent reading the code decreases (PT).

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Implications for Software Cost Estimation (1)
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Implications for Software Cost Estimation (2)
Person-Month Allocation
Conditions without Readability Considerations
TOTAL PROJECT COST WITHOUT READABILITY
CONSIDERATIONS 4,284,500
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Implications for Software Cost Estimation (3)
Conditions without Readability Enhancement
TOTAL PROJECT COST WITH READABILITY ENHANCEMENTS
3,727,515