Conference PaperPDF Available

Impact of Overtime and Stress on Software Quality

Authors:

Abstract

Producing software requires an environment conducive to concentration and measured work. In this paper several projects are presented with varying degrees of overtime where the resultant quality of the applications in terms of defect counts varies directly. It is proposed that stress in the work environment driven by overtime adversely affects software quality.
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Impact of Overtime and Stress on
Software Quality
Balaji Akula & James Cusick
Wolters Kluwer Corporate Legal Services
New York, NY
{balaji.akula, james.cusick}@wolterskluwer.com
ABSTRACT
Producing software requires an environment conducive to concentration
and measured work. In this paper several projects are presented with
varying degrees of overtime where the resultant quality of the applications
in terms of defect counts varies directly. It is proposed that stress in the
work environment driven by overtime adversely affects software quality.
Introduction
Stress can be defined as any type of change that causes physical, emotional or
psychological strain. (Scott, E., 2007). From time to time stress overwhelms us, in many
cases this is indeed normal (hr.blr.com, Oct 2006). While it is virtually impossible for
most people to eliminate stress we can certainly take steps to avoid stress and its potential
to cause debilitating side effects where possible. According to Peggy Duncan (Scott,
2007), stress is caused due to a number of factors: disorganization, unclear goals, too
many personal phone calls, disjointed processes, no routines, poor planning,
procrastination, lack of focus, and lack of training are some of the reasons for stress.
Statistical data from the National Institute for Occupational Health and Safety has
disclosed that the number of American workers who consider stress to be a major
problem in their lives has more than doubled during the past ten years
(Missoncontrol.com, Sep 9 2007). Among professions, software engineering can produce
stressful environments for its participants. In this paper the relationship of stressors to
software quality is explored.
2
Background
As a starting point the question was asked, what is the one thing that can cause a high
number of defects and do so repeatedly? There is no single answer to this question. Some
of the reasons include but are not restricted to the lack of proper requirements change
process, technical challenges, aggressive schedule, improper planning, stress, etc. This
paper focuses on the impact of stress on the quality of product developed by software
engineers over a period of 2 years. Any stress related health issues were not studied and
are not reported here. The background for this effort stemmed from a high number of
defects noticed during quality assurance of the software lifecycle.
We have made an attempt to establish a link between an aggressive schedule and its
negative impact on software quality. The general pattern of this linkage is given below:
Aggressive Schedule Overtime Stress Defects
As per the above pattern, Defects will increase when a team is working on an aggressive
schedule. Putting teams under pressure leads to increases in overtime thus reducing
concentration on quality and more focus on output. In general mental activity and clarity
is required for any mind (Jeffries, E.R 2007). The more overtime the worker spends
means that his mental activity and clarity decreases while stress increases. As
corroborated by data presented in this paper it is proposed that defects are injected as a
result of stress caused due to overtime. Moreover as per recent studies a tired/stressed
programmer has double the chances of putting in a very serious bug but has probably also
put in a much higher percentage of smaller ones (Jeffries, E.R 2007).
Defects are a very important metric in software engineering. When defects are taken out
of context it gives a bad impression of the product in question. However, when taken as a
whole, along with the project, the number of lines of code that is written, project
duration, etc., it may not prove to be the demon that it is usually made out to be. Poor
quality can act as a dampener in the following ways:
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1) Can allow teams to deviate from core project activities
2) Can result in loss of trust between QA & Development teams
3) Increased stress during triage where defects are discussed, and in some cases
can have a personal effect detrimental to project.
4) Worst case may result in delay of the project.
5) Finger pointing over defects among teams kills the team spirit.
6) Teams end up spending more time fixing defects than developing business
critical features.
One of the most important reasons that stress is generated, according to our observations,
is due to aggressive schedules especially being repeated project after project. While many
project team members (the average age of the team member was 26 years) can absorb the
health related issues of stress; their productivity suffers and manifests in the form of
defects (read as poor quality). We have studied 4 projects over a period of 2 years and
have observed the defect levels for each of the projects. All projects had a few
similarities; all were web applications built using Microsoft .NET 2.0 technologies, 3 out
of the 4 projects had an aggressive schedule, and all were completed as planned, 3
projects had a high defect rate. The results are provided below.
Results
Data on four projects were analyzed. The amount of scheduled work hours, actual
overtime hours, and number of defects were recorded on each of these production
releases. The overtime hours were seen as a reliable indicator of stress on the project
team members and the level of defects was seen as an output of the stress on the project
team members. In the diagrams below the actual data is reported from these commercial
projects.
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Effort, Overtime, and Defect Levels
0
100
200
300
400
500
600
700
800
900
Project 1Project 2Project 3Project 4
Project
Hours
0
500
1000
1500
2000
2500
Defects
Estimated
Overtime
Defects
Fig 1: Project wise Effort, Overtime and Defects levels
It is proposed that high stress levels results in less quality and that high stress levels can
been produced by high overtime. This observation is evident in Figure 1. As can be seen
from the graph (actual data is provided in Table 1), the defect levels are low when
overtime is lower or zero. Figure 1 plots the estimated hours for each project and the
actual overtime hours for each project. Additionally, the line plot indicates the level of
defects for each project. As can be seen, the projects with overtime had higher defect
rates.
OverTime Report
0
100
200
300
400
500
600
700
800
900
Project1 Project 2 Project 3 Project 4
Project Wise OT (hrs)
Estimated Time (hrs)
Estimated Hours
Avg. OT / Person
5
Fig2: Overtime hours spent on each project
The Graph in Figure 2 depicting the actual estimated time for construction and overtime
effect on the team to complete project on time and as planned. Please also refer to the
same in table format (Table 1). In most cases overtime runs at 10% of the estimated effort
hours. Specifically, overtime ran at 150 to 200 hours per person on these projects. These
projects are executed with a construction phase of usually 8 weeks plus an additional 8
weeks of QA. Thus, the projects are executed in a compressed time frame using overtime
work to balance for the aggressive scheduling.
Project PROJECT 1 PROJECT 2 PROJECT 3 PROJECT 4
Estimated
person hours 784 416 416 528
Overtime
person Hours 175 167 0 198
Defects 2038 1545 142 2000
Table1. Table data of Project wise defect count in relation to overtime.
Observations
From the above results, the following can be observed
¾ Defect counts increases when overtime is extensive.
¾ Stress on workers, and on Projects (via defects, delay etc) develops when projects
are not planned and executed properly (that is, with excessive use of overtime).
In general overtime may be requested under the following conditions:
¾ To accommodate Changes/Requirements not in original estimates.
¾ Natural/unprepared calamities like viral outbreak, snowstorm etc.
¾ Technical challenges that cause delays in implementation.
¾ Under estimation
If a project has clocked overtime not due to any of the above reasons then the primary
cause could well be due to incorrect planning. By incorrect planning it could mean
that the estimates were aggressive or planning itself was way off the mark. From the
6
above data in table 1, it appears that the latter was the case, as barring ARWR2 all
projects required overtime to complete as planned.
While it is comforting to note that the projects were completed on time, the stress
factor to developers/project team is largely ignored as the team moves on to the next
project or is consumed by other activities. Whatever the case the stress is continued
from one project to another, as history repeats itself time after time.
A correlation of 0.98 (between overtime data and defect count) clearly indicates the
effect of overtime driven stress on increased defect count. The defect count in
PROJECT 3 is only 7% when compared to the average defect counts of other
releases. The possible reason for PROJECT 3 having low defects and high quality can
be adduced to the following:
¾ Zero overtime hours spent during project.
¾ Correct Planning and Estimation
There are alternative ways to interpret this data. One way of viewing this data is that the
defects themselves lead to overtime which leads to stress. The question would be what
leads to the defects in the first place. A second alternate view is around the volume of
software being written. In this view since the more code that is written generates more
defects then the high level of production of code leads to more defects which leads to
overtime. These and other alternate views may have validity but they were not deeply
considered, instead the primary view of this paper remains that aggressive scheduling
drives defect levels which drives overtime.
Conclusion
More and more industries are looking at ways to reduce workplace stress; however the
big question is how to accomplish this effectively and efficiently. By neglecting or not
paying enough attention to workplace stress companies will end up nullifying their
investment. The evidence that links stress to poor quality has been shown above. Critics
7
will argue that other factors also play a role in the quality of software products. There is
no question about this premise. However, stress is one of the important factors that can
lead to bad quality products as we have shown. According to Michael Beck (2005)
productivity drops significantly when we are under stress and our ability to think clearly
is impacted. A survey conducted in October 2006 indicates a loss of 1 hour or more per
day in productivity due to stress (hr.blr.com, Oct 2006). As the saying goes it is better to
strike when the iron is hot. So act now.
Some of the important lessons that can be learned are
¾ Avoid stress to improve productivity.
¾ Plan and do not under-plan or be too aggressive.
¾ Estimation approach – we can revisit the estimation practice that is followed
and improve if required. We should try to follow what is in the estimate and
try not to cut down on the same for whatever reasons.
¾ Defect prediction – Using our experience gained from previous projects it
would make sense to predict the defect density based on estimation,
component inventory, and previous data so that we can adjust our estimates
accordingly.
¾ Quality development – we should strive to go for quality and avoid
development during QA phase of the lifecycle. As mentioned below the cost
of fixing defect is not only high but the probability of introducing new defects
is high too.
Both the above are easy to avoid in most scenarios. The exception being projects which
are designated as “Fast Track” and is aggressive from the beginning. The benefits are
huge. I would imagine that the following would benefit software teams in the short and
long term if implemented according to the nature of project:
1. Less stress to software engineer results in more productivity.
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2. Less stress means low defects and indirectly less wrangling with the QA/
Project Management during triage. We are all aware of the battles between QA
and Software Engineering teams. We can channel all the energy to good use
instead of wrangling over defects.
3. Having a plan which has a buffer (say 2 weeks for example) is better than under-
planning. Experienced Software developers are aware that the requirements keep
changing, and/or new requirements keep cropping all the time. Hence having a
buffer of a few weeks helps the project and in no way would delay the same.
4. It's well-established that it takes less time and costs much less to prevent defects
than to fix them. A recent article in Crosstalk, the Journal of Defense Software
Engineering, reports that "finding and fixing bugs is the most expensive cost
element for large systems and takes more time than any other activity." (Jeffries,
E.R, 2007)
5. Last but not the least by planning with the human factor in mind we will be
appreciated for trying a humane approach to software development. There is
sufficient stress in globally outsourced development without driving overtime
hours skyward.
9
References
1. http://hr.blr.com/news.aspx?id=19241. October 13, 2006, Survey: Workplace Stress
Has Substantial Impact on Productivity.
2. Elizabeth, Scott - http://stress.about.com/od/managementtools/a/peggyinterview.htm,
09/20/2007, An Interview with Productivity Expert Peggy Duncan.
3. Jeffries, E Ronald - http://www.xprogramming.com/xpmag/jatSustainablePace.htm,
2007. Viewed on Oct 16 2007.
4. http://www.missioncontrol.com/p_mcsys_stress.htm, 09/20/2007, How does stress
Impact Productivity. – Last line, Para 1.
5. Beck, Michael - Manage Stress to Boost Productivity, 2005
http://www.xleaders.com/Articles/Beck/Manage%20Stress%20to%20Boost%20Prod
uctivity.pdf. Viewed on Oct 15 2007.
Further Reading
1. http://main.uab.edu/show.asp?durki=57296 - Ten Ways to Control Stress
2. http://www.webmd.com/anxiety-panic/guide/tips-to-control-stress - Mental Health:
Tips to Control Stress
3. http://www.drake.co.nz/dbr/pdf/work_place_stress.pdf. - When Workplace Stress
stifles productivity.
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... Akula and Cusick [13] carried out a statistical survey on four real-life software projects to analyze the impact of overtime on software quality. The number of scheduled work hours, actual overtime hours, and a number of defects were recorded on each of the projects. ...
... Results from experiments revealed that the approach is significantly better than standard NSGA-II in 76% of experiments and significantly outperformed standard overtime planning strategies used in the industry. However, their formulation failed to assess the negative effect of overtime on software quality even when empirical studies in the literature [11,13] have revealed that the effort required to correct additional errors introduced by developers working overtime outweighs the productivity gains. ...
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... Progress equals fast, and fast equals success, which is a recipe for addiction [Bro14]. In addition to the known effects of stress on software quality as evaluated by Akula and Cusick [AC08], Amin et al. [ABHR11] found that occupational stress also negatively affects knowledge sharing, which leads to long-term detrimental effects for software systems development, particularly in global development settings. ...
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... They also observed an increase in equilibrium-and motorrelated problems on Japanese workers from the IT sector subjected to long shifts [24]. Regarding the outcome of developers' work, Akula and Cusick [4] and DeMarco [10] relate overtime work with higher error generation rates in software projects. DeMarco and Lister [11] also relate excessive overtime with increased personal attrition, which may reduce knowledge exchange amongst developers [27] and hamper the ability of a company to hold expertise and properly deal with developer turnover [2]. ...
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This document accumulates the bibliographic references utilized in the collected publications of the author over a 35-year period from 1985 to 2020. This inventory reflects over 100 research papers, articles, presentations, and multiple books covering a multi-disciplinary research background touching on over 300 keywords. The total number of bibliographic items derived from these artifacts exceeds 750 references presented in 34 separate ontological categories or topical domains. Researchers, instructors, or students looking to discover a focused yet extensive and diverse set of bibliographic references in one easy to navigate document can apply this collection to their work. Within this collection are citations ranging from Galileo in the year 1638 to a new technology publication from 2020. The topics also range widely across the following major subject areas: 1) Software Engineering, IT Operations, Cybersecurity, Quality, Reliability; 2) Management; 3) Organizational Psychology; 4) History of Science; 5) Political Economy; 6) Japanese Art, Culture, and History; and 7) Ornithology. The import, then, of this document is to not only provide useful reference information but to underscore the importance of research materials, research libraries, online research repositories, and the cycle of publication to the ongoing advancement of Science.
  • Michael - Beck
Beck, Michael -Manage Stress to Boost Productivity, 2005 http://www.xleaders.com/Articles/Beck/Manage%20Stress%20to%20Boost%20Prod uctivity.pdf. Viewed on Oct 15 2007.
  • Michael-Manage Beck
Beck, Michael-Manage Stress to Boost Productivity, 2005 http://www.xleaders.com/Articles/Beck/Manage%20Stress%20to%20Boost%20Prod uctivity.pdf. Viewed on Oct 15 2007.