Rqmts & OO

(Textual) Requirements Assistant*

Hayes: works on repositories of textual documents (requirements, designs, failure reports, …)

Scale: readily works with CM1 (in MDP)

Nikora: works on repositories of textual requirementsScale: studies of 1300+ requirements

WH

AT

Automate onerous yet important tasks related to requirements tracing

Hayes: well-chosen modest linguistic processing; trainable from user inputs; thorough, thoughtful metrics

Nikora: scripts to automate search (pattern-based), closure (of tracing graph), comparison (of result sets); identifies the frequency of various expressive styles

HO

WW

HY

* akin to the “Apprentice” name used by Rich, Waters & Reubenstein

RE

TR

O tool – com

ing soon to the SA

RP

site!Are the days of textual requirements numbered? (e.g., by “model based”)

Rqmts & OO

Analyst’s Assistant

Menzies: where models exist, subsumes “heuristic” activities (debugging, diagnosis, optimization, tuning…)

Scale: no fear! Adoptability: taught to students

Powell: property validation of designs expressed in formal model including C code Scale: MER arbiter; Adoptable: 3rd party experimenter

WH

AT

Analysis results for the masses – timely, scalable, meaningful

Menzies : random search; simple yet expressive language; underlying language mechanism

Powell : utilizing LURCH (David Owen), in turn based on Menzies’ ideas; bugs’ connection to code obvious

HO

WW

HY

but am *I* too old to learn?

Are models really going to be prevalent as we think?

Rqmts & OO

Designer’s Assistant

Whittle: assists in progression of requirements, use cases, scenarios, design; Applicability: event driven systems UML

Scale: 10 dense pages of requirements, 40 scenarios

Beimes : Model checking of interface (proper use of: OS calls, sequencing; synchronization, commanding)

Applicability: interfaces, including those of COTSScale: CM1 study; VxWorks study results imminent

WH

AT

Help do/check design

Whittle : prioritize among use cases; elicit off-nominal scenarios; form relationships among scenarios; generalize scenarios to state machines

Beimes : Model checking, static analysis platform; control-flow graph; properties easily expressed (C like language, plus standard templates)

HO

WW

HY

Systems, Interfaces, COTS

Rqmts & OO

OO Metrician’s Assistant

Lateef : Critiquing of use cases and beyond Application: attitude control system; OO models

Etzkorn : semantic metrics (ignores syntactic variability), Application: works on OO designs before code existsScale: (anyone contemplating working with 20CDRoms’ worth of data does not fear scale…)

WH

AT

Help measure/validate OO designs

Lateef : OO-specific risks; prioritization of critical (essential) use cases, etc.; OO metrics; BBN model to combine multiple metricsEtzkorn : leverage significant prior work on program understanding (conceptual graphs for knowledge representation); empirical and comparative comparisons

HO

WW

HY

Early days of NASA mission use of OO; perception of increase – correct?

Rqmts & OO

Obstacles

Information access: Foreign Nationals & ITAR, etc.“Sanitizer”: Helps, but sometimes discardsinformation needed for study; MDP helps

Challenge: Getting enough case studies

SARP quarterly reporting more onerous than NSF (but not DARPA or DoD):Can be discouraging/daunting to typical academics

However, NASA cares:University thrilled by visit from NASA!

Ominous trend: level of documentation in average project is decreasing.

Forthcoming NPR may remedy this, but its effect still several years in future; also, beware of old and unaudited information

*SARP complaint

line

Rqmts & OO

Publicationilty a problem? Apparently not.

Credibility: Nicely documents past successes, key to gaining interest of future customers!

SARP values them: Called for in quarterly report; published impact ratings for venues (conferences, journals); AWARD!

Outreach: via SARP web site!

SARP : SARP encourages empiricism* (application and evaluations), key to (e.g.) experience paper Note: may need longer lead time for release approvalNASA source of real problems, which researchers

QUESTION: Is there a NASA strategy for (e.g.) conference participation?

*Empirically based work: new territory for some Recommended reading: Basili, Selby & Hutchins, TSE, 1986

Rqmts & OO

Aunt Aardvark's Advice Column*:“Working with projects”

Initially: $: Pay for time of project personnelGets you the data/insight/feedbackGets you an inside advocateHowever, you’re often their lowest priority task

Having established credibility: Offer technique to project, in return for their supply of, and guidance on, their data

Interactions: Make few rather than many queries of project; be willing to wait; formulate query to be of interest (address significant issues)

Free: Offer free for experimentation / limited time use

Pitfalls: Don’t force your process on the user(s) Anticipate (& prepare for) how your tool will be used

(in ways you could hardly imagine!!!)

*SARP quarterly

newsletter

Rqmts & OO

QUESTIONS

Is it better to solve a new problem than to improve upon an old solution?

“Lines in the sand” – is anyone going the same way?

What NEW tools would we wish for?

It’s like asking what requirements are we missing…

What is the SARP product (or products)?

Should we have a common goal (or few goals)?

E.g., multiple SARP projects working towards a single tool/process/course/…

SARP is for reporting out – what about reporting in to SARP?