1 Motivation and Challenges
2 Background and Terminology
3 Related Work
Study | A | Motivation | Support | E | C | R |
---|---|---|---|---|---|---|
Surveys | ||||||
Austin and Graeme (1993) | = | LoEv | Interviews | ⋅ | ⋅ | |
Snook and Harrison (2001) | = | LoEv | Interviews | ⋅ | ||
Oliveira (2004) | = | Edu./Train. | Course websites | ⋅ | ||
Woodcock et al. (2009)a | = | LoEv | Interviews | ⋅ | ||
Davis et al. (2013) | + | TechTx | Interviews | ⋅ | ⋅ | |
Liebel et al. (2016) | + | LoEv | Online questionnaire | ⋅ | ||
Ferrari et al. (2019) | + | TechTx | Literature study | ⋅ | ||
Literature Studies and Summaries | ||||||
Wing (1990) | + | SotA | O/E | ⋅ | ⋅ | |
Bloomfield et al. (1991) | = | SotA | ⋅ | |||
Fraser et al. (1994) | = | TechTx | ⋅ | |||
Heitmeyer (1998) | = | TechTx | ⋅ | |||
Gleirscher et al. (2019) | + | TechTx | SWOT analysis | ⋅ | ⋅ | |
Expert Opinions and Experience Reports | ||||||
Jackson (1987) | = | TechTx | ⋅ | |||
Bjorner (1987) | = | TechTx | ⋅ | |||
Barroca and McDermid (1992) | = | SotA | Multiple cases | ⋅ | ||
Bowen and Hinchey (1995a) | + | Hyp. Testing | ⋅ | |||
Bowen and Hinchey (1995b) | + | TechTx | ⋅ | |||
Hinchey and Bowen (1996) | – | TechTx | ⋅ | |||
Heisel (1996) | + | TechTx | ⋅ | |||
Holloway and Butler (1996) | + | LoEv | ⋅ | |||
Lai (1996) | + | TechTx | ⋅ | |||
Bowen and Hinchey (2005) | + | Hyp. Testing | Literature study | ⋅ | ||
Parnas (2010) | = | TechTx | ⋅ | ⋅ | ||
Case Studies and Experiments | ||||||
Gerhart and Yelowitz (1976) | = | LoEv | Multiple cases, O/E | ⋅ | ⋅ | ⋅ |
Hall (1990) | + | Hyp. Testing | O/E | ⋅ | ||
Craigen et al. (1995)b | + | SotA | Multiple cases, O/E | ⋅ | ||
Knight et al. (1997) | = | TechTx | Field experiment | ⋅ | ||
Pfleeger and Hatton (1997) | = | Hyp. Testing | Effect analysis | ⋅ | ||
Sobel and Clarkson (2002) | = | Hyp. Testing | Lab experiment | ⋅ | ||
Miller et al. (2010) | = | TechTx | Multiple cases, O/E | |||
Klein et al. (2018) | + | TechTx | ⋅ | |||
Chudnov et al. (2018) | = | TechTx | ⋅ |
4 Research Method
4.1 Research Goal and Questions
4.2 Construct and Link to Research Questions
Concept | Id. | Description [Scale] | Point [Question] |
---|---|---|---|
Measured twice\(\dots \) | |||
Domain | C1 | Application domains of FMs [MC among domains] | Past [Q1], Intent [Q8] |
Role | C2 | Role in using FMs [MC among roles] | Past [Q4], Intent [Q9] |
Use | C3 | Use of FMs [experience level/relative frequency per FM | Past [Q5/Q6], Intent |
class] | [10/11] | ||
Purpose | C4 | Purpose of using FMs [absolute/relative frequency per purpose] | Past [Q7], Intent [Q12] |
Measured once \(\dots \) | |||
Experience | C5 | Level of FM experience [duration ranges in years] | Single [Q2] |
Motivation | C6 | Motivation to use FMs [degree per motivational factor] | Single [Q3] |
Obstacles | C7 | Difficulty of obstacles to using FMs [degree per challenge] | Single [Q13] |
4.3 Study Participants and Population
4.4 Survey Instrument: On-line Questionnaire
Id. | Question or question template | Scale (see Table 4) | Sec. | Fig. |
---|---|---|---|---|
Q1 | In which application domains (C1) in industry | MC among domains or academia have you mainly used FMs? | 5.2 | |
Q2 | How many years of FM experience (including the study of FMs, C5) have you gained? | Duration range in years | 5.2 | |
Q3 | Which have been your motivations (C6) to use FMs? | Degree per motivational factor | 5.2 | |
Q4 | In which roles (C2) have you used FMs? | MC among roles | 5.3 | |
Q5 | Describe your level of experience (C3) for 〈class of formal description techniques〉. | Level of experience per class | 5.3 | |
Q6 | Describe your level of experience (C3) for | Level of experience per class 〈class of formal reasoning techniques〉. | 5.3 | |
Q7 | I have mainly used FMs for (C4) ... | Absolute frequency per purpose | 5.3 | |
Q8 | In which domains (C1) in industry or academia do you intend to use FMs? | MC among domains | 5.4 | |
Q9 | In which roles (C2) would (or do) you intend to use FMs? | MC among roles | 5.4 | |
Q10 | I (would) intend to use (C3) 〈class of formal description techniques〉〈this〉 often. | Relative frequency per class | 5.4 | |
Q11 | I (would) intend to use (C3) 〈class of formal reasoning techniques〉〈this〉 often. | Relative frequency per class | 5.4 | |
Q12 | I (would) intend to use FMs for (C4) 〈purpose〉. | Relative frequency per purpose | 5.4 | |
Q13 | For any use of FMs in my future activities, I consider 〈obstacle〉 (C7) as 〈that〉 difficult. | Degree of difficulty per obstacle | 5.5 |
Name | Values | Type |
---|---|---|
degree of motivation | “no motivation”, “moderate motivation”, “strong motivation (or requirement)” | L3 |
degree of | “not as an issue.”, “as a moderate challenge.”, “as a tough challenge.”, | L3 |
difficulty | “I don’t know.” | |
experience level | “I do not have any knowledge of or experience in FMs.”, “less than | O |
(duration-based) | 3 years”, “3 to 7 years”, “8 to 15 years”, “16 to 25 years”, “more than 25 years” | |
experience level | “no experience or no knowledge”, “studied in (university) course”, | O |
(task-based) | “applied in lab, experiments, case studies”, “applied once in engineering, practice” “applied several times in engineering practice” | |
frequency (absolute) | “not at all.”, “once.”, “in 2 to 5 separate tasks.”, “in more than 5 separate tasks.” | O |
frequency (relative) | “no more or not at all.”, “less often than in the past.”, “as often as in the past.”, “more often than in the past.”, “I don’t know.” | L3 |
choice | single/multiple: (ch)ecked, (un)checked | N |
4.5 Data Collection: Sampling Procedure
4.6 Data Evaluation and Analysis
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describing the challenge difficulty ratings after associating one of (1) domain, (2) motivational factor, (3) role, (4) purpose, and (5) FM class with challenge (C7) and
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distinguishing (1) more experienced (ME, > 3 years) from less experienced respondents (LE, ≤ 3 years), (2) practitioners (P, practised at least once) from non-practitioners (NP, not used or only in course or lab), (3) motivated (M, moderately or strongly motivated by at least one specified factor) from unmotivated respondents (U, no motivating factor specified), (4) respondents’ past and future views, and (5) respondents with increased usage intent (II) from ones with decreased usage intent (DI).
likert
, gplots
, and ggplot2
and some helpers from the “Cookbook for R” and the “Stack Exchange Stats” community5). Content analysis and coding takes place in a spreadsheet application. A draft of Appendix A has been archived in Gleirscher and Marmsoler (2018).5 Execution, Results, and Analysis
5.1 Survey Execution
Channel type | Examples & references |
---|---|
General panels | SurveyCircle, www.surveycircle.com |
LinkedIn groups | E.g. on ARP 4754, DO-178, FME, ISO 26262 |
Mailing lists | E.g. system safety (U Bielefeld, formerly U York) |
Newsletters | BCS FACS; GI RE, SWT, TAV |
Personal pages | E.g. Facebook, Twitter, LinkedIn, Xing |
ResearchGate | Q&A forums on www.researchgate.net |
Xing groups | E.g. Safety Engineering, RE |
5.2 Description of the Sample (Answering RQ 1)
5.3 Facets of Formal Methods Use (Answering RQ 1)
5.4 Past Use Versus Usage Intent (Answering RQ 2)
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CBs show slightly more frequently an increased intent (the “more often” group) than MBs; for both sub-groups, respondents with 2 to 5 and with more than 5 past uses.
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MBs show slightly more frequently a decreased intent (the “no more” group) than CBs.
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MBs show slightly more frequently an increased intent than CBs when looking at respondents who have used FMs more than 5 times. However, MBs indicate slightly less frequently an increased intent than CBs when looking at respondents with 2 to 5 uses.
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CBs indicate more dnk s after 2 to 5 uses and slightly more frequently a decreased intent after 5 uses in comparison with MBs.
5.5 Perception of Challenges (Answering RQ 3)
Challenge name & description | Src. | Supported by (oldest, newest) | Findings for RQ3 (Section 5.5) |
---|---|---|---|
Scalability: Useful in handling large and technologically heterogeneous systems | Q | toughest in Fig. 16; by Ps more than by NPs; when using FMs for assurance and clarification; independent of FM class | |
Skills & Education: Methods known (little misconception); trained and experienced users available | Q | 2nd toughest; agreed by LEs and MEs; largely independent of FM class; comparatively small tough-proportions by Ms | |
Transfer of Proofs: Relation between models and reality (e.g. code), handling incomplete specifications | Q | Agreed by LEs and MEs; top-rated by DIs and NMs; largely independent of FM class | |
Reusability: Parametric proofs, reusable specifications and verification results | Q | Top-rated by tool provider stakeholders and lectures | |
Abstraction: Useful and correct (automated) abstractions from irrelevant detail (for comprehension and | Q | Varies notably across FM classes validation) | |
Tools & Automation: Useful notations and trustworthy tools (for manipulation, checking, collaboration, documentation) | Q | Top-rated by DIs; but comparatively small tough-proportions from practitioners | |
Maintainability: Stable proofs, easily modifiable specifications, and adaptable verification results | Q | Comparatively small tough-proportions from practitioners | |
Resources: Sufficient resources, good cost-benefit ratio (despite adoption, training, licenses) | 4R | No detailed data was collected: Because these challenges were mentioned several times each, we classify them to be at least of moderate difficulty. | |
Process Compatibility: Integration into existing process, method culture, standards, and regulations | 6R | ||
Practicality & Reputation: Benefit awareness and sufficient empirical evidence for benefits | 7R |
6 Discussion
6.1 Findings and Their Interpretation
RQ1: In which typical domains, for which purposes, in which roles, and to what extent have | |
FMs been used? | |
F1 | Intrinsic motivation to use FMs is stronger than norms or codes of regulatory authorities. |
F2 | The fraction of respondents with no experience at all is comparatively low. |
F3 | Respondents use FMs the least in computational engineering and for dynamical systems. |
RQ2: Which relationships can we observe between past experience in using FMs and intent to use FMs? | |
F4 | Increased intent to use FMs observable across all application domains. |
F5 | Amount of experience is positively associated with the strength of usage intent. |
F6 | The responses do not show any significant differences between code- and model-based FMs. |
F7 | Respondents show high likelihoods of an increased intent to use FMs such as |
“model checking” or “assertion checking” in areas such as “transportation” or “critical infrastructures”. | |
RQ3: How difficult do study participants perceive widely known FM challenges? | |
F8 | Scalability and skills & education lead the challenge difficulty ranking. |
F9 | Maintainability of proof results is found to be the least worrying challenge. |
F10 | Reusability of proof results is rated as tough by several practitioner groups. |
F11 | FM users with decreased usage intent rate tool deficiencies as their top obstacle. |
F12 | Respondents identified resources, process compatibility, and reputation as further obstacles. |
F13 | All considered challenges are generally perceived as moderate or tough. |
F14 | Among the FM classes, process models are most positively associated with tough scalability. |
RQ4: What can we say about the perceived ease of use and the perceived usefulness of FMs? | |
F15 | Respondents perceive the usefulness of FMs as mainly positive and intend to increase their use. |
F16 | Respondents perceive the ease of use of FMs as mainly negative. |
Relationship to Existing Evidence (from the literature): | |
F17 | Proof maintainability and reusability are least covered by the literature. |
F18 | We repeat Austin and Graeme (1993), excluding benefit analysis but with |
a broader sample and more detailed questions. |
6.2 Relationship to TAM for Methods (Answering RQ 4)
6.3 Relationship to Existing Evidence
6.4 Threats to Validity
6.4.1 Construct Validity
6.4.2 Internal Validity
6.4.3 External Validity
6.4.4 Reliability
7 Conclusions
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Intrinsic motivation is stronger than the regulatory one.
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Despite the challenges, our respondents show an increased intent to use FMs in industrial contexts.
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Past experience is correlated with usage intent.
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All challenges were rated either moderately or highly difficult, with scalability, skills, and education leading. Experienced respondents rate challenges as highly difficult more often than less experienced respondents.
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From the literature and the responses, we identified three additional challenges: sufficient resources, process compatibility, good practicality/reputation.
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The negative responses to the questions about obstacles to FM effectiveness suggest that the ease of use of FMs is perceived more negative than positive.
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Gaining experience and confidence in the application of a FM seems to play a role in developing a positive perception of usefulness of that FM.
Another respondent noted:“Well chosen questions which do not leave me guessing. Relevant to future FM research and practice.”
Only one participant found the questionnaire difficult for FM beginners.“Thank you very much for this survey. It is very constructive and important. It handles most of the issues encountered by any practitioner and user of FMs.”